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https://github.com/Doragd/Algorithm-Practice-in-Industry
搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）
https://github.com/Doragd/Algorithm-Practice-in-Industry
Last synced: about 2 months ago
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搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）
- Host: GitHub
- URL: https://github.com/Doragd/Algorithm-Practice-in-Industry
- Owner: Doragd
- License: bsd-2-clause
- Created: 2023-01-30T12:31:51.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-13T04:44:20.000Z (5 months ago)
- Last Synced: 2024-04-14T01:04:33.417Z (5 months ago)
- Language: Python
- Size: 271 MB
- Stars: 1,503
- Watchers: 41
- Forks: 207
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- my-awesome - Doragd/Algorithm-Practice-in-Industry - 09 star:2.2k fork:0.3k 搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号） (Python)
README
# Algorithm-Practice-in-Industry
## 仓库介绍
**一开始这个仓库是做如下内容：**
搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）
- [搜广推大厂实践文章](https://github.com/Doragd/Algorithm-Practice-in-Industry#%E5%A4%A7%E5%8E%82%E5%AE%9E%E8%B7%B5%E6%96%87%E7%AB%A0)
> 本文仅做资源收集，未引用具体内容，如有侵权，请联系删除。
> 源文件：source.xlsx，可以执行自定义排序
随后扩展了以下内容：
- [搜广推论文推送Bot](https://github.com/Doragd/Algorithm-Practice-in-Industry/tree/main#%E6%90%9C%E5%B9%BF%E6%8E%A8%E8%AE%BA%E6%96%87%E6%8E%A8%E9%80%81bot)
- [搜广推顶会论文列表](https://github.com/Doragd/Algorithm-Practice-in-Industry#%E9%A1%B6%E4%BC%9A%E8%AE%BA%E6%96%87%E5%88%97%E8%A1%A8)
- [搜广推优质博主文章](https://github.com/Doragd/Algorithm-Practice-in-Industry/blob/main/%E6%90%9C%E5%B9%BF%E6%8E%A8%E4%BC%98%E8%B4%A8%E5%8D%9A%E4%B8%BB%E6%96%87%E7%AB%A0.md)
- [搜广推算法系列串讲](https://github.com/Doragd/Algorithm-Practice-in-Industry/blob/main/%E6%90%9C%E5%B9%BF%E6%8E%A8%E7%AE%97%E6%B3%95%E7%B3%BB%E5%88%97%E4%B8%B2%E8%AE%B2.md)
## 贡献新文章
提交issue，利用github action自动更新readme和source.xlsx内容
已提供issue模板，具体内容参考issue：https://github.com/Doragd/Algorithm-Practice-in-Industry/issues/1
## 一起交流
* 关于我：2023届毕业，之前做NLP方向，毕业后转去搜广推方向，一枚努力适应的菜鸡。目前在做召回方向。
* 我的论文阅读笔记：https://github.com/doragd/paperreading
* 和我交流：
## 搜广推论文推送Bot
* Arxiv论文：利用github action + 彩云小译 + 飞书机器人每天推送cs.IR和cs.CL的新论文到飞书群组中。[配置文件](https://github.com/Doragd/Algorithm-Practice-in-Industry/blob/main/.github/workflows/push_arxiv_daily.yml)
* 顶会论文：利用github action + 彩云小译 + 飞书机器人每天推送搜广推顶会的论文到到飞书群组中。[配置文件](https://github.com/Doragd/Algorithm-Practice-in-Industry/blob/main/.github/workflows/push_conf_daily.yml)
* PS: 虽然论文没太大用，但是可以无聊时候刷刷，扩展下思路。
* 比如早上通勤的时候，可以刷刷推送，看看有没有有意思的论文，也不需要花太多时间，毕竟摘要都翻译好了~
## 顶会论文列表
| CIKM | ECIR | KDD | RECSYS | SIGIR | WSDM | WWW |
| ------ | ------ | ------ | ------ | ------ | ------ | ------ |
| [2012](./papers/cikm/cikm2012.md) | [2012](./papers/ecir/ecir2012.md) | [2012](./papers/kdd/kdd2012.md) | [2012](./papers/recsys/recsys2012.md) | [2012](./papers/sigir/sigir2012.md) | [2012](./papers/wsdm/wsdm2012.md) | [2012](./papers/www/www2012.md) |
| [2013](./papers/cikm/cikm2013.md) | [2013](./papers/ecir/ecir2013.md) | [2013](./papers/kdd/kdd2013.md) | [2013](./papers/recsys/recsys2013.md) | [2013](./papers/sigir/sigir2013.md) | [2013](./papers/wsdm/wsdm2013.md) | [2013](./papers/www/www2013.md) |
| [2014](./papers/cikm/cikm2014.md) | [2014](./papers/ecir/ecir2014.md) | [2014](./papers/kdd/kdd2014.md) | [2014](./papers/recsys/recsys2014.md) | [2014](./papers/sigir/sigir2014.md) | [2014](./papers/wsdm/wsdm2014.md) | [2014](./papers/www/www2014.md) |
| [2015](./papers/cikm/cikm2015.md) | [2015](./papers/ecir/ecir2015.md) | [2015](./papers/kdd/kdd2015.md) | [2015](./papers/recsys/recsys2015.md) | [2015](./papers/sigir/sigir2015.md) | [2015](./papers/wsdm/wsdm2015.md) | [2015](./papers/www/www2015.md) |
| [2016](./papers/cikm/cikm2016.md) | [2016](./papers/ecir/ecir2016.md) | [2016](./papers/kdd/kdd2016.md) | [2016](./papers/recsys/recsys2016.md) | [2016](./papers/sigir/sigir2016.md) | [2016](./papers/wsdm/wsdm2016.md) | [2016](./papers/www/www2016.md) |
| [2017](./papers/cikm/cikm2017.md) | [2017](./papers/ecir/ecir2017.md) | [2017](./papers/kdd/kdd2017.md) | [2017](./papers/recsys/recsys2017.md) | [2017](./papers/sigir/sigir2017.md) | [2017](./papers/wsdm/wsdm2017.md) | [2017](./papers/www/www2017.md) |
| [2018](./papers/cikm/cikm2018.md) | [2018](./papers/ecir/ecir2018.md) | [2018](./papers/kdd/kdd2018.md) | [2018](./papers/recsys/recsys2018.md) | [2018](./papers/sigir/sigir2018.md) | [2018](./papers/wsdm/wsdm2018.md) | [2018](./papers/www/www2018.md) |
| [2019](./papers/cikm/cikm2019.md) | [2019](./papers/ecir/ecir2019.md) | [2019](./papers/kdd/kdd2019.md) | [2019](./papers/recsys/recsys2019.md) | [2019](./papers/sigir/sigir2019.md) | [2019](./papers/wsdm/wsdm2019.md) | [2019](./papers/www/www2019.md) |
| [2020](./papers/cikm/cikm2020.md) | [2020](./papers/ecir/ecir2020.md) | [2020](./papers/kdd/kdd2020.md) | [2020](./papers/recsys/recsys2020.md) | [2020](./papers/sigir/sigir2020.md) | [2020](./papers/wsdm/wsdm2020.md) | [2020](./papers/www/www2020.md) |
| [2021](./papers/cikm/cikm2021.md) | [2021](./papers/ecir/ecir2021.md) | [2021](./papers/kdd/kdd2021.md) | [2021](./papers/recsys/recsys2021.md) | [2021](./papers/sigir/sigir2021.md) | [2021](./papers/wsdm/wsdm2021.md) | [2021](./papers/www/www2021.md) |
| [2022](./papers/cikm/cikm2022.md) | [2022](./papers/ecir/ecir2022.md) | [2022](./papers/kdd/kdd2022.md) | [2022](./papers/recsys/recsys2022.md) | [2022](./papers/sigir/sigir2022.md) | [2022](./papers/wsdm/wsdm2022.md) | [2022](./papers/www/www2022.md) |
| [2023](./papers/cikm/cikm2023.md) | [2023](./papers/ecir/ecir2023.md) | [2023](./papers/kdd/kdd2023.md) | [2023](./papers/recsys/recsys2023.md) | [2023](./papers/sigir/sigir2023.md) | [2023](./papers/wsdm/wsdm2023.md) | [2023](./papers/www/www2023.md) |
| 2024 | [2024](./papers/ecir/ecir2024.md) | 2024 | 2024 | 2024 | [2024](./papers/wsdm/wsdm2024.md) | [2024](./papers/www/www2024.md) |
## 大厂实践文章
| 公司 | 内容 | 标签 | 时间 |
| ------------ | ------------------------------------------------------------ | ------------- | ---------- |
| 百度 | [多域图大模型在百度推荐系统的实践与思考](https://mp.weixin.qq.com/s/6qanJ1tfV9AJF-Qbamezww) | 图推荐 | 2024-05-09 |
| 百度 | [百度推荐资源冷启动实践](https://mp.weixin.qq.com/s/_3CkflIJtsyndBqHhm8w3Q) | 冷启动 | 2024-05-09 |
| 小红书 | [小红书高时效推荐系统实践：从系统提效到内容冷启动](https://www.bilibili.com/video/BV1B142167Hu) | 冷启动 | 2024-05-07 |
| 美团 | [大众点评内容搜索算法优化的探索与实践](https://mp.weixin.qq.com/s/4gki0Ju82HnHV5Qze2faBw) | 搜索 | 2024-03-21 |
| 美团 | [百亿大规模图在广告场景的应用](https://mp.weixin.qq.com/s/RCOcFFIYDylWg10ZG72_KA) | 图 | 2024-03-28 |
| 360 | [360信息流推荐Mind召回](https://mp.weixin.qq.com/s/Hy9yZ8yOF2FwQ9FIn3DQTw) | 召回 | 2024-01-19 |
| 百度 | [百度搜索Push个性化](https://mp.weixin.qq.com/s/nly7Za8Ei29lx6HBuimBTQ) | 搜索 | 2024-01-17 |
| 小红书 | [小红书推荐用户及内容冷启动实践](https://www.bilibili.com/video/BV1fe41127m1) | 冷启动 | 2024-01-12 |
| 百度 | [百度feed图模型演进](https://mp.weixin.qq.com/s/k78RRpvDrP3GlsdBV3B3sg) | 推荐 | 2024-01-11 |
| 百度 | [百度推荐排序技术的思考与实践](https://mp.weixin.qq.com/s/JTNmYJNgoQr26fkT-Oy35g) | 推荐 | 2024-01-07 |
| OPPO | [OPPO 广告召回算法实践与探索](https://mp.weixin.qq.com/s/4TtGHY3Rc9Ui_1jkOKSx5Q) | 召回 | 2023-12-30 |
| 美团 | [美团交易视频推荐探索与实践](https://www.bilibili.com/video/BV1N64y1H7mc) | 推荐 | 2023-12-23 |
| 美团 | [内容搜索算法优化的探索与实践](https://www.bilibili.com/video/BV1Yb4y137a3) | 搜索 | 2023-12-23 |
| 得物 | [粗排优化探讨｜得物技术](https://mp.weixin.qq.com/s/JX8adK0y-AtsoRRxx4734Q) | 粗排 | 2023-12-20 |
| 百度 | [百度视频推荐跨域多目标预估与融合的实践和思考](https://mp.weixin.qq.com/s/YXPmZn3ujbBavFsmnf5Vzw) | 推荐 | 2023-11-29 |
| 腾讯 | [AI大模型「改造」QQ浏览器搜索](https://mp.weixin.qq.com/s/DSfo8AXIV_QMyBX4EOfe7A) | 搜索 | 2023-11-19 |
| 阿里妈妈 | [HC^2：基于混合对比学习的多场景广告预估建模](https://mp.weixin.qq.com/s/8Mg3lt4t2j5dtFKCsRet4g) | 广告 | 2023-11-15 |
| 阿里 | [融合复杂目标且支持实时调控的重排模型](https://mp.weixin.qq.com/s/kRmTthX9jLB8sHC32UJWfw) | 召回 | 2023-11-14 |
| 网易 | [网易云音乐推荐系统的冷启动技术](https://mp.weixin.qq.com/s/EDkoe3nxvQ_24nxC8ktd7g) | 冷启动 | 2023-11-10 |
| 华为 | [多任务和多场景在华为推荐系统中的应用](https://mp.weixin.qq.com/s/c7xO71NEE2n-RbtRKItA) | 推荐 | 2023-11-09 |
| 阿里妈妈 | [BOMGraph：基于统一图神经网络的电商多场景召回方法](https://mp.weixin.qq.com/s/Grd0PyAYmrlvc6SQLASFrg) | 召回 | 2023-11-01 |
| 小红书 | [小红书推荐系统创新性探索](https://www.bilibili.com/video/BV1Zz4y1P7Tx) | 冷启动 | 2023-10-31 |
| 爱奇艺 | [爱奇艺效果广告双出价优化历程](https://mp.weixin.qq.com/s/brTPvcm6_yjwoXAme2kUdA) | 广告 | 2023-10-20 |
| 快手 | [快手内容冷启动推荐模型实践](https://mp.weixin.qq.com/s/8MKoANEAw687FoeTasngpA) | 冷启动 | 2023-10-11 |
| 百度 | [百度推荐排序技术的思考(提取码:r5kv)](https://pan.baidu.com/s/1kTbebwkDuZOuKS7INW1Jew) | 推荐 | 2023-08-26 |
| 新浪 | [推荐系统大模型启发的MemoNet(提取码:ckpa)](https://pan.baidu.com/s/1iR6tdrD93o35WPKyievo7w) | CTR预估 | 2023-08-26 |
| 网易 | [网易云音乐推荐的多模态冷启技术(提取码:x72d)](https://pan.baidu.com/s/1PnE89HVWg379ax9ewP8ydQ) | 冷启动 | 2023-08-26 |
| 快手 | [快手内容冷启动模型实践(提取码:cjbc)](https://pan.baidu.com/s/1SbDA0t6DzevVcVEzttfydg) | 冷启动 | 2023-08-26 |
| 百度 | [百度视频推荐跨域多目标预估与融合的实践和思考(提取码:cva3)](https://pan.baidu.com/s/1nVoJCVUQZDGxlf05zhYuhw) | 多目标 | 2023-08-26 |
| 虎牙 | [面向直播场景的虎牙排序算法实践(提取码:yhb8)](https://pan.baidu.com/s/1iU4LNm7qFAKUtkE65hVaYg) | 排序 | 2023-08-26 |
| 58同城 | [深度学习在互联网房产推荐场景的算法实践(提取码:wcz7)](https://pan.baidu.com/s/1LGmN8ZUajMBhnZ7vcOaRoA) | 排序 | 2023-08-26 |
| 京东 | [图机器学习在京东视频召回中的应用(提取码:gfkx)](https://pan.baidu.com/s/1-NQEP8M4Y1GH1gzMGj7p-Q) | 召回 | 2023-08-26 |
| 百度 | [图模型在百度推荐系统的实践与思考(提取码:huaz)](https://pan.baidu.com/s/1tzWEjphTt9EzTXqp4OfiRw) | 推荐 | 2023-08-26 |
| 百度 | [百度新资源冷启动实践(提取码:bji6)](https://pan.baidu.com/s/12GAalYfn4TuHf-8dZ9qHLA) | 冷启动 | 2023-08-26 |
| 蚂蚁 | [图算法在蚂蚁集团营销推荐场景的应用(提取码:xvvi)](https://pan.baidu.com/s/1AilbuaTQLtrHOegjK353_Q) | 推荐 | 2023-08-26 |
| 百度 | [百度凤巢大模型与搜索广告满意度设计与实践](https://mp.weixin.qq.com/s/Mpi7wZlHw3eKPJzj00CPMw) | 搜索 | 2023-08-13 |
| 美团 | [美团外卖推荐关于用户新颖体验优化的技术探索](https://mp.weixin.qq.com/s/RG_eOhxJxzdou06GfJVp3g) | 推荐 | 2023-07-20 |
| 美团 | [美团外卖智能陪伴型导购的探索与实践](https://mp.weixin.qq.com/s/prLykt36ONu43V-twgfcOg) | Query推荐 | 2023-07-13 |
| 京东 | [京东搜索EE链路演进](https://mp.weixin.qq.com/s/na90G1GqLoS41L_-NHpVKQ) | 搜索生态 | 2023-07-12 |
| 阿里妈妈 | [基于特征自适应的多场景预估建模](https://mp.weixin.qq.com/s/dDHdQFBoSTxIE_M_hPSh5w) | 多场景排序 | 2023-07-05 |
| 阿里妈妈 | [转化率预估新思路：基于历史数据复用的大促转化率精准预估](https://mp.weixin.qq.com/s/MRpoM1ucZIVdiXMcS4PiHQ) | 推荐 | 2023-06-28 |
| 腾讯 | [对话双塔——腾讯视频中的粗排相关性模型](https://mp.weixin.qq.com/s/ETJ-lkIKcxN6zIgH8FrTjw) | 粗排相关性 | 2023-06-28 |
| 小米电商 | [多任务学习梯度冲突在电商场景的改进](https://mp.weixin.qq.com/s/0GWkUFSC0geRZMpISx-4gg) | 多任务学习 | 2023-06-24 |
| 阿里妈妈 | [排序和准度联合优化：一种基于混合生成/判别式建模的方案](https://mp.weixin.qq.com/s/kMEYxeUPtJIbJ-X6NgHR2A) | 排序 | 2023-06-21 |
| 小红书 | [语义模型在小红书社区搜索的应用(提取码:xfkv)](https://pan.baidu.com/s/1xQ5lqxYb_VvLxLIzDPgMHQ) | 搜索 | 2023-06-17 |
| 蚂蚁 | [支付宝搜索的Query理解与语义召回技术(提取码:p6gc)](https://pan.baidu.com/s/12Q_QisYd8GFq-pXX3g1x5w) | 召回 | 2023-06-17 |
| 阿里淘系 | [Generator-Evaluator重排模型在淘宝流式场景的实践](https://mp.weixin.qq.com/s/YoQNDdsRE6LZWJXrRKubLw) | 重排 | 2023-06-09 |
| 得物 | [得物多场景统一推荐技术演进](https://mp.weixin.qq.com/s/Aj5rY1ziLqvPnZ6zNAHvFw) | 推荐 | 2023-06-09 |
| 阿里 | [阿里解耦域适应无偏召回模型详解](https://mp.weixin.qq.com/s/0Cbc3aAYTeFqLDutLBXJmA) | 召回 | 2023-06-04 |
| Shopee | [多任务学习最新进展：基于神经元级共享的 CTR、CVR 多任务联合预估方法](https://mp.weixin.qq.com/s/4PO6EK3b4VCKO0ibd76C9w) | 推荐 | 2023-05-29 |
| 阿里妈妈 | [AdaSparse: 自适应稀疏网络的多场景CTR预估建模](https://mp.weixin.qq.com/s/a2X08FZfMgMfzmucF0DZ_w) | 精排 | 2023-05-10 |
| 得物 | [得物App相关推荐价格体验优化](https://mp.weixin.qq.com/s/J9gEmRWsjE8eZHpHvSHOlQ) | 推荐 | 2023-05-10 |
| 阿里淘系 | [淘宝内容化推荐场景下对多场景全域表征的思考与应用](https://mp.weixin.qq.com/s/e6Sqb6MAY5Bvzd7Pi8-zOg) | 推荐 | 2023-04-28 |
| 阿里飞猪 | [因果推断技术在飞猪保险模块推荐以及可解释性应用](https://mp.weixin.qq.com/s/M9RSzYiDvJ8L2Ux2VmFFRw) | 推荐 | 2023-04-28 |
| 阿里淘系 | [每日好店——店品排序探索模型升级](https://mp.weixin.qq.com/s/rdcqehk6l_GMF07YisHLFw) | 推荐 | 2023-04-24 |
| 微博 | [微博推荐实时大模型的技术演进](https://mp.weixin.qq.com/s/wRi0YJLpru5M1My0H2Ww0w) | 推荐 | 2023-04-24 |
| 阿里健康 | [阿里可解释性推荐算法应用](https://mp.weixin.qq.com/s/hQgsT9xpQr2Ylb6_3uwfvQ) | 推荐 | 2023-03-06 |
| Shopee | [Calibration4CVR：2018年关于“神经元级别共享的多任务CVR”的初探](https://mp.weixin.qq.com/s/2JFY--9xDoMF5_2YCehwkg) | 推荐 | 2023-03-05 |
| 得物 | [得物社区推荐精排模型演进](https://mp.weixin.qq.com/s/tX8fq3Az_n5NcnPlEpzA-Q) | 推荐 | 2023-01-11 |
| 阿里妈妈 | [阿里妈妈展示广告召回之多场景建模算法](https://mp.weixin.qq.com/s/LH4XI9DZXq77NvSvaoYfLQ) | 召回 | 2022-12-07 |
| 美团 | [大规模异构图召回在美团到店推荐广告的应用](https://mp.weixin.qq.com/s/9HZZQCVd-bMRrR6mCanaog) | 召回 | 2022-11-24 |
| 美团 | [美团外卖搜索基于Elasticsearch的优化实践](https://mp.weixin.qq.com/s/6k8THshasaYfSaLr58O1NA) | 搜索 | 2022-11-17 |
| 美团 | [图技术在美团外卖下的场景化应用及探索](https://mp.weixin.qq.com/s/7bCrFHNeQ3_2kLlvzb5l3w) | 搜索 | 2022-09-08 |
| 得物 | [得物分类TAB商品流多目标排序模型的演进](https://mp.weixin.qq.com/s/URIjMVSA4gJ6EBWk4Tp6tA) | 推荐 | 2022-07-01 |
| 得物 | [得物多兴趣召回模型实践](https://mp.weixin.qq.com/s/oEcreSx5_XsN9x4Nkv7cOw) | 推荐 | 2022-05-18 |
| 得物 | [得物社区推荐多目标排序初探](https://mp.weixin.qq.com/s/3_RmSyl_3wIAH3lW_XKEyA) | 推荐 | 2021-12-27 |
| 阿里 | [CMDM：基于异构序列融合的多兴趣深度召回模型在内容平台的探索和实践](https://mp.weixin.qq.com/s/IwzizxkRQbo1Kv28wVGQag) | 召回 | 2021-12-07 |
| 爱奇艺 | [爱奇艺搜索排序算法实践](https://mp.weixin.qq.com/s/gvFagKMgGKE2ZFic1znQWg) | 搜索 | 2021-07-30 |
| 爱奇艺 | [多目标排序在爱奇艺短视频推荐中的应用](https://mp.weixin.qq.com/s/JOQdyQDCFStWXdxTckUa5Q) | 搜索 | 2021-06-25 |
| 爱奇艺 | [爱奇艺短视频推荐技术中多兴趣召回技术的演变](https://mp.weixin.qq.com/s/T2G8L820haEbvXgryvEWHg) | 召回 | 2021-04-23 |
| 爱奇艺 | [如何提升链路目标一致性？爱奇艺短视频推荐之粗排模型优化历程](https://mp.weixin.qq.com/s/LZlskUK4dmOd5fLTZIATnQ) | 粗排 | 2021-02-26 |
| 阿里淘系 | [淘宝个性化推荐中自适应与无监督的多场景模型建模实践](https://mp.weixin.qq.com/s/KX2gmEUme4Iy1PCR9PTrYg) | 推荐 | 2023-04-10 |
| 阿里淘系 | [每日好店——淘宝店铺推荐系统实践](https://mp.weixin.qq.com/s/DCiNgI1LL-uN4JmgQ5VSjQ) | 推荐 | 2023-04-07 |
| 小红书 | [搜推系统召回阶段的前沿进展](https://www.bilibili.com/video/BV1Km4y167ho) | 召回 | 2023-04-03 |
| 阿里飞猪 | [飞猪旅行场景下的实时用户理解服务](https://mp.weixin.qq.com/s/CFmp_FTHbf5l2ohUokTGgw) | 搜索 | 2023-04-01 |
| 美团 | [多场景多任务学习在美团到店餐饮推荐的实践](https://mp.weixin.qq.com/s/v-GN1ors-bWutfsIJcZYbQ) | 推荐 | 2023-03-23 |
| 小红书 | [小红书高时效推荐系统背后的技术升级](https://mp.weixin.qq.com/s/1a2bl983bGKM713xI_3v_A) | 推荐 | 2023-03-21 |
| 阿里妈妈 | [代码开源！阿里妈妈展示广告Match底层技术架构最新进展](https://mp.weixin.qq.com/s/IoPZ-fUL0h1PVOA8uDXPJg) | 召回 | 2023-03-14 |
| 阿里妈妈 | [贝叶斯分层模型应用之直播场景打分校准](https://mp.weixin.qq.com/s/-klZWT30J41xPQfOqlWiNA) | 精排 | 2023-03-14 |
| 腾讯音乐 | [粗排上不了COLD？我们提出了异构三塔粗排](https://zhuanlan.zhihu.com/p/611877625) | 粗排 | 2023-03-07 |
| 美团 | [交互式推荐在外卖场景的探索与应用](https://mp.weixin.qq.com/s/SwR1-mAtqjwsnJVy3UiMnA) | 推荐 | 2023-02-16 |
| 小红书 | [小红书广告智能创意能力构建过程详解](https://mp.weixin.qq.com/s/EabcwCtSPEmFOjRATVVORQ) | 广告 | 2023-02-16 |
| 快手 | [快手精排模型实践](https://mp.weixin.qq.com/s/SsgVqei9sL5y7N1GUXOJLg) | 精排&CXR预估 | 2023-02-01 |
| 阿里健康 | [领域知识增强的预训练语言模型在药电商搜索领域的实践](https://mp.weixin.qq.com/s/or9DT2HlVPnUFBsqAEv6Uw) | 搜索 | 2023-01-30 |
| 京东 | [京东零售在电商搜索场景下的数据科学实践](https://mp.weixin.qq.com/s/Rmgh-ynoWU4uerh_4jL4YA) | 搜索 | 2023-01-29 |
| 阿里达摩院 | [基于预训练语言模型的行业搜索的应用和研究](https://mp.weixin.qq.com/s/oRxn2PQdh3_giCPkrJpQaQ) | 搜索 | 2023-01-28 |
| 阿里飞猪 | [深度召回在飞猪旅行推荐系统中的探索和实践](https://mp.weixin.qq.com/s/AyMmfixX8rXUgGIf94uBkw) | 召回 | 2023-01-25 |
| 腾讯QQ浏览器 | [QQ浏览器搜索相关性技术演进](https://mp.weixin.qq.com/s/rF9wC2qecPHDcn8fy6KIuA) | 搜索相关性 | 2023-01-18 |
| 小米 | [小米电商算法秘籍：移花接木-新模型如何热启动快速超越线上旧模型](https://mp.weixin.qq.com/s/_lEeyyxhGHg5ZOtrpf2epQ) | 推荐&CXR预估 | 2023-01-11 |
| 阿里健康 | [阿里健康医药电商搜索相关性实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247621853&idx=1&sn=61378cddef3e7b9579b00f92d4e3c609&chksm=fbd6aeb1cca127a76b85c8af5ba05d2b9f482252d176be3c6b42a8081bd4589f96c6178e066f&scene=27#wechat_redirect) | 搜索相关性 | 2023-01-11 |
| 网易 | [云音乐评论内容理解技术](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247487662&idx=1&sn=f3f28448bc605c8022cc84c3093f6562&chksm=ea2e6788dd59ee9e1111e3352363aa86bb8abdaa92f8167df62c201783bee38647912691ebe9&mpshare=1&scene=1&srcid=0117adz8z5uuqKd4JsFiqBky&sharer_sharetime=1673958834277&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 内容理解 | 2023-01-10 |
| 阿里淘系 | [深度统一粗排在淘宝主搜索的优化实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650490509&idx=1&sn=0881c47b13cf7d97a1f91e7b5830c58d&chksm=83978e95b4e007830bcd4bae627b02b275baf60b453035a711e43f4ff604c5389ed089ef2c45&scene=27#wechat_redirect) | 粗排 | 2023-01-06 |
| 网易 | [云音乐视频搜索优化之旅](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247487588&idx=1&sn=099b6105ef6f4e06df3ec6ace9cea168&chksm=ea2e6742dd59ee54d426895b8c2c335e7bed3027da1302da81eea829e26bb1600c7d149f29f6&mpshare=1&scene=1&srcid=0117wGK8qD3vbVGyqHjrC0m2&sharer_sharetime=1673958824881&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 搜索 | 2023-01-04 |
| 快手 | [金雅然：因果推断主要技术思想与方法总结](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247618221&idx=1&sn=bbbb4acd59fa304fd9941138d03a5b03&chksm=fbd6bcc1cca135d72d19924659d0ba226d516409c975610d077e64705d351b2c0b82ee46da4f&scene=27#wechat_redirect) | 因果推断 | 2022-12-26 |
| 度小满 | [因果推断在度小满金融场景的应用探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247617404&idx=1&sn=a21ed8b66d98c7f2c32605a8ed5b6e7c&chksm=fbd6b910cca13006bf965630fcacedaf4ef4342b5b85f2a2728b83ff2e671fc2422c6d9a8583&scene=27#wechat_redirect) | 因果推断 | 2022-12-22 |
| 小红书 | [小红书广告投放机制详解，如何用算法实现全站自动化投放](http://mp.weixin.qq.com/s?__biz=Mzg4OTc2MzczNg==&mid=2247486087&idx=1&sn=fa6b75242336d49fb780ab63c63ce4e5&chksm=cfe7a870f89021667d5056c587fdd9aafa025de8443fe9496f5321ff729b93536545324235b9&mpshare=1&scene=1&srcid=0117WqeEpkGzXEGbrlQ2qUP5&sharer_sharetime=1673957656684&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 广告 | 2022-12-15 |
| 小米 | [小米电商推荐算法CVR模型实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247614845&idx=1&sn=0e8c26b62cd8e2ffe5c54e6e3ee28a5d&chksm=fbd6b311cca13a07f68d47ac22d2ebc0f2fad1e082809bd0ccc8f68a5bc6f298e2bc16fa0ec1&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-12-07 |
| bilibili | [百亿数据个性化推荐：弹幕工程架构演进](http://mp.weixin.qq.com/s?__biz=Mzg3Njc0NTgwMg==&mid=2247492039&idx=1&sn=1395b05f9f13d2ec5f094098335f0fb2&chksm=cf2f24e2f858adf401be214e3c00a17e71b4580afa3bb7c2e479fbdd196abaced8836c4bfc04&mpshare=1&scene=1&srcid=01173Yirag3aRdwVVXpLoC6m&sharer_sharetime=1673957819680&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2022-11-25 |
| 腾讯 | [带你走进 Redis](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649774611&idx=1&sn=50784f8f205424ac315c214eecde370d&chksm=beccc96889bb407e2fd0af67766bebc8e01a6619ac8356dba71efeb165c450b97c7a5561d5ef&scene=27#wechat_redirect) | 工程相关 | 2022-11-22 |
| 网易 | [机器学习模型在云音乐指标异动预测的应用实践](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247487245&idx=1&sn=e60203a06dfbbd736ba5085554a8e86a&chksm=ea2e782bdd59f13d0cf199247081e406ef3352c2e211fe24be3aa851d996f37d412bb232f6ea&mpshare=1&scene=1&srcid=0117PDLkxZZZqZuhvqAb5zCN&sharer_sharetime=1673958990974&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 数据科学 | 2022-11-18 |
| 腾讯 | [因果推断在腾讯游戏中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247609347&idx=1&sn=277d03dd9bbd978c2d6fa564e6ea3583&chksm=fbd69e6fcca117797939d7386d642cd99eca8bbe9d25b02e3fcf5245eb871faf4fcf9bffc5bc&scene=27#wechat_redirect) | 因果推断 | 2022-11-12 |
| 小红书 | [首次解密小红书“种草”机制：大规模深度学习系统技术是如何应用的](http://mp.weixin.qq.com/s?__biz=Mzg4OTc2MzczNg==&mid=2247485593&idx=1&sn=80a57bc832565f38dfea8ce396975c3b&chksm=cfe7aa6ef890237880872ebe8ff471a9642104d84a6a3463ba4ea81a304f15fde179c437e741&mpshare=1&scene=1&srcid=0117HHDQtSslzh1IBwT4tYom&sharer_sharetime=1673957674492&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2022-11-11 |
| 网易 | [网易严选跨域多目标算法演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247607759&idx=2&sn=793f2f26ca50fdcdd5e1805c540a8844&chksm=fbd697a3cca11eb5b0967e15bd56f2adfb8691d96e78a6b5115dd7bf96c30078ddaa9ed6eee4&scene=27#wechat_redirect) | 多目标&多任务 | 2022-11-01 |
| NVIDIA | [NVIDIA Merlin HugeCTR 推荐系统框架介绍](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247607015&idx=1&sn=640758c804a49c7fee278066b85203df&chksm=fbd6908bcca1199d272fe7ca3e6c7cde7dcdb43f33fbfc319fca414f76f5f3dc97ca443cb178&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-10-31 |
| 快手 | [快手异质性因果效应模型构建及应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247605093&idx=1&sn=32663a66325e7d0f5d8e4164ead40cc4&chksm=fbd6e909cca1601feba78e308e77e54d4860e7a08b5407c02cab0be27ec555f83647d2933209&scene=27#wechat_redirect) | 因果推断 | 2022-10-29 |
| 阿里 | [阿里 DeepRec 大规模稀疏模型训练推理引擎（文末附PPT下载）](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247603217&idx=1&sn=a170a798db5c190fef89b28a4c157aa1&chksm=fbd6e67dcca16f6b0e825f6818c40b67e38827aba0686d1a8221eda050b81196c45bf62ab643&scene=27#wechat_redirect) | 工程相关 | 2022-10-21 |
| 小红书 | [上干货！小红书“薯条”业务竞价策略及最优公式详解](http://mp.weixin.qq.com/s?__biz=Mzg4OTc2MzczNg==&mid=2247485120&idx=1&sn=d34d4cca4ad1ec00b1772d9ca4f7da5e&chksm=cfe7a437f8902d21404e7e184f8da18d6ed8b3056af83574060dbfedac20677b490b04c796fc&mpshare=1&scene=1&srcid=0117Of6uG80CLb3wppixoYYu&sharer_sharetime=1673957705690&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 广告 | 2022-10-19 |
| 美团 | [预训练语言模型压缩、双塔蒸馏在美团上的落地实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247599652&idx=1&sn=7e548fdf373404f9e28a68ed60ed5fdf&chksm=fbd6f448cca17d5eb554161219b8c926861540ebf6a6c405e0d9397f7a857109adfef6712b38&scene=27#wechat_redirect) | 召回 | 2022-10-10 |
| 美团 | [知识图谱在美团搜索酒旅场景认知中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247598912&idx=1&sn=f9b89d6ab0e471ad3d0a5274c521fd76&chksm=fbd6f12ccca1783a70ecc2434b5614bad885fe8a4070a7b028432034c472a36763c0624d4abb&scene=27#wechat_redirect) | 搜索 | 2022-09-30 |
| 腾讯QQ浏览器 | [搜索场景下的智能实体推荐](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247597380&idx=1&sn=4db0d3fe68ca96bdf1f5304e3bf27efe&chksm=fbd6cf28cca1463eda0a8c82b5d5bac1c52980c18c4b3503ae7ba1f785b28a486d4e1569a730&scene=27#wechat_redirect) | 搜索 | 2022-09-26 |
| 美团 | [美团基于知识图谱的个性化新闻推荐系统](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247597321&idx=1&sn=250130a92dc6fa4fcded1633faa5c908&chksm=fbd6cf65cca1467362fe21eaef511502e03412b93fbef8256174d3ce5f90360ed7c112c1ea0a&scene=27#wechat_redirect) | 推荐 | 2022-09-25 |
| 腾讯 | [腾讯图神经网络与推荐预训练模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247595912&idx=1&sn=d6d805fca059e98542d139238a64de65&chksm=fbd6c5e4cca14cf266926db0859a3f06611e4ec36c359ccc6f1ad3a1689b6d77edcb3eb5a553&scene=27#wechat_redirect) | 推荐&图网络 | 2022-09-19 |
| 蚂蚁 | [图机器学习在蚂蚁集团推荐业务中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247595831&idx=1&sn=6527aef4ce07e8ce2867af62d27338cb&chksm=fbd6c55bcca14c4d83907a730d8ab95cef14a86ae7d3e834c41aaea74bedb38cd73cdfc7f35e&scene=27#wechat_redirect) | 推荐&图网络 | 2022-09-18 |
| 华为 | [华为图神经网络在推荐系统中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247594776&idx=1&sn=494824ef9ea3be55df7fe98211c3964e&chksm=fbd6c174cca148623cfada0a0539a0d33b173d01bbf36fef508f4f9c2a1618bc856785651ac3&scene=27#wechat_redirect) | 推荐&图网络 | 2022-09-10 |
| 阿里 | [推荐算法中的特征工程](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247593010&idx=1&sn=f9384194319269e7a79ba8e577830ce4&chksm=fbd6de5ecca1574819e4184b92b5167e1317cc226ba1673f57f22cf544bd30b6cc55a97f6bce&scene=27#wechat_redirect) | 推荐&特征工程 | 2022-08-30 |
| 阿里淘系 | [连续迁移学习跨域推荐排序模型在淘宝推荐系统的应用](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650472691&idx=1&sn=0de2198074b629ad7c9605a7a3d7d683&chksm=8397c8ebb4e041fde5b09d0496f18224248a922b5559f5722c914c856fda59d3f9283834f292&scene=27#wechat_redirect) | 推荐&跨域 | 2022-08-30 |
| 虎牙 | [虎牙直播用户增长中台算法与工程实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247592677&idx=2&sn=3cae00c17a89b7f34b65bd835a553491&chksm=fbd6d889cca1519fba25525dbff8f189be084c6a0bd4a30489aa5facde7038bcd663617ce393&scene=27#wechat_redirect) | 用增 | 2022-08-27 |
| 腾讯音乐 | [吴喆：全民K歌直播推荐系统详解](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247591189&idx=1&sn=b6d191ff2cf27e4c9bfef945683bfb4a&chksm=fbd6d779cca15e6f195c83f5c873a5ecb364478c75282dd6bde34986a089e0b443ec659724fd&scene=27#wechat_redirect) | 推荐 | 2022-08-22 |
| 网易 | [云音乐播放页直播推荐实战](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247486879&idx=1&sn=6ed863ec4ebb4a43fd5303dc31283e96&chksm=ea2e7ab9dd59f3af6c20ff794907160342ea844097f787a8b6761872cbe2a047a43272b542bb&mpshare=1&scene=1&srcid=0117V5aFvFP5Ddjfi2srfCOV&sharer_sharetime=1673959633475&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2022-08-17 |
| 美团 | [美团搜索粗排优化的探索与实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651770506&idx=2&sn=53df7e69852b53b8e9a78704250a3f59&chksm=bd1217c78a659ed1fe25caf2f387dd5adf7543c0d18aa9404a68dedc4393d3f75bdbc08d0097&mpshare=1&scene=1&srcid=0117rkw4ucCVdx40VXlSeHoB&sharer_sharetime=1673956974542&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 粗排 | 2022-08-11 |
| 腾讯 | [一文搞懂 Redis 架构演化之路](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649772002&idx=1&sn=7ab50931711fa4cebae08db9b132ade5&chksm=beccdc9989bb558f3223ecfec306aacfa4c17cdd49dab60bc6bd70be72b61d79d319c4e7b025&scene=27#wechat_redirect) | 工程相关 | 2022-07-26 |
| 腾讯 | [无量深度学习系统在腾讯推荐类业务的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247586109&idx=1&sn=0ee0886b4f9249baf93439835d5d0268&chksm=fbd62351cca1aa47003a2abcd486f152e3eb2a70de6313764c24518b8ff41e0e1a654aef8bd3&scene=27#wechat_redirect) | 推荐 | 2022-07-08 |
| 美团 | [大众点评搜索相关性技术探索与实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651769715&idx=2&sn=2d6c3eb9d9646374b5f789fcf4282794&chksm=bd12123e8a659b2841fd12d873d3f7087f300b3bf8b6cbd9136728fc1231655eb573cf97f4e0&mpshare=1&scene=1&srcid=0117Xd442BpulsuEWGrZhqzJ&sharer_sharetime=1673957035636&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 搜索相关性 | 2022-07-06 |
| 蚂蚁 | [蚂蚁超大规模商家知识图谱构建及其融合应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247584814&idx=1&sn=0905e790e129fc69071ee35b033580f0&chksm=fbd63e42cca1b7544faa0cb1e8bced4ba70991deb29679987616565a0e7e66e31ca926b65538&scene=27#wechat_redirect) | 知识图谱 | 2022-07-01 |
| 网易 | [云音乐FeatureStore建设与实践](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247486528&idx=1&sn=af5d722949e17ef6388582cb79d8db39&chksm=ea2e7b66dd59f27040aeffc48f0dea150e5bc52a4e3d1b3cba7f1c9cf4ad4588d7e0c5e1a0de&mpshare=1&scene=1&srcid=0117qiTM67fWa7TSJSplzmZm&sharer_sharetime=1673959054283&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐&特征工程 | 2022-06-29 |
| 京东 | [揭秘京东广告精排百分位AUC提升技术方案](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247502484&idx=1&sn=72e86c400261dceb2526e4de6759e73f&chksm=a691b97991e6306fea07ccc0fe69fc2c21e41d6dcf5696b0558d38a06773799073a78e227bfd&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-06-29 |
| 阿里飞猪 | [章凡：飞猪基于因果推断技术的广告投后归因](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247583653&idx=1&sn=5dc8cfa18b3a48103ba104470df2be45&chksm=fbd635c9cca1bcdf262951910a8b0808d395a5a00f34e47c38adcf6e8eac1c8c1a61780ba514&scene=27#wechat_redirect) | 因果推断 | 2022-06-27 |
| 京东 | [吕豪：京东搜索EE场景排序链路升级实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247583047&idx=1&sn=e1d82adf00fc6259a3750228d6979b4c&chksm=fbd6372bcca1be3dc6577ef0b2b3d671f12ab72ef7347202df175e19132433d4aefdeb97505f&scene=27#wechat_redirect) | 搜索 | 2022-06-24 |
| 美团 | [端智能在大众点评搜索重排序的应用实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651769148&idx=2&sn=f046a03fe1a02abf525c065963ae4038&chksm=bd1210718a65996725b53e639b2b6c3b51eb28f9ac53152a1c695746cf1c15d202535ee5f71f&mpshare=1&scene=1&srcid=0117F7qqsflxxpqhdQ1SngCz&sharer_sharetime=1673957044472&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 重排 | 2022-06-16 |
| 网易 | [云音乐预估系统建设与实践](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247486449&idx=1&sn=489c7b0383800ddcc36a9a72af81f3c3&chksm=ea2e7cd7dd59f5c15d2ed2adcd1db35f89d92c8390ed956f0b298a658def93410a4c6668f715&mpshare=1&scene=1&srcid=0117rJEidptu50XAatgGRbHk&sharer_sharetime=1673958981682&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 精排&CXR预估 | 2022-06-15 |
| 腾讯微信 | [微信开源大规模embedding训练推理框架](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247502213&idx=1&sn=fc146301867e6dcfc1c76eb4ead978d0&chksm=a691ba6891e6337e86096af1a44fc35fbbf5ec1c3af779b4bf84d00dc5738ceb80acfadd3df4&scene=27#wechat_redirect) | 召回 | 2022-06-15 |
| 美团 | [张鸿志：美团大脑百亿级知识图谱的构建及应用进展](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247577711&idx=1&sn=d4dc3ecc9fc9c63aa0a7746237156800&chksm=fbd60203cca18b153440f5ea638f0f409fa953c06ce8bcf1b23878664617dc206947ca7e4fa8&scene=27#wechat_redirect) | 知识图谱 | 2022-06-03 |
| 快手 | [快手牛亚男：基于多Domain多任务学习框架和Transformer，搭建快手精排模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247577501&idx=1&sn=0abd962b316235700f4050fcc8968a3b&chksm=fbd61df1cca194e7df8a414a8055df18e3592e0b59a1f941afb05005221e8e168f99a8d18b62&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-06-01 |
| 阿里淘系 | [SIGIR2022 \| 流行度偏差如何利用？探索解耦域适应无偏召回模型](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650464730&idx=1&sn=c5aa5396fc7c7a2eabb7990c6ce0d178&chksm=839629c2b4e1a0d491b314e5d6437ca87083de35cfa3791cf00a3fbd559641159cd0d350d057&scene=27#wechat_redirect) | 召回 | 2022-05-31 |
| 阿里淘系 | [多模态技术在淘宝主搜召回场景的探索](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650464165&idx=1&sn=76193b6fc997e3d1d842c6ebe2dbf317&chksm=839617bdb4e19eabccf0bd4bc71d89e97cb17def86abb812a562b4019d379525e33ff7339152&scene=27#wechat_redirect) | 召回 | 2022-05-27 |
| 京东 | [陈宏申：浅谈京东电商商品文案挖掘难点与优化实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247576281&idx=2&sn=097528a2c3a4ba819eab3cd122df990b&chksm=fbd618b5cca191a394aec5846ce48720d95e3e6ea153c0770452a0eec447309383b3bf99e453&scene=27#wechat_redirect) | 文案挖掘 | 2022-05-25 |
| 华为 | [华为朱杰明：预训练模型在信息流推荐中的应用与探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247575814&idx=1&sn=c20d71bcf94a88a3e791885edb1af421&chksm=fbd61b6acca1927c038e60999db375f0192b322e72bf094e764a295f36ec217d8651d4a41a2c&scene=27#wechat_redirect) | 推荐 | 2022-05-22 |
| 网易 | [NUMA架构下的预估系统性能优化](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247486273&idx=1&sn=b0866d0b104de68bb5866b879df5baf5&chksm=ea2e7c67dd59f57161d5651396274ac15cd9af031995650a7e349710e983ed1a20d4f2a74fbd&mpshare=1&scene=1&srcid=0117G8EkbjLIyTRHBJSunt4X&sharer_sharetime=1673959041521&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 工程相关 | 2022-05-19 |
| 小红书 | [小红书信息流推荐多样性解决方案](http://mp.weixin.qq.com/s?__biz=Mzg4OTc2MzczNg==&mid=2247484208&idx=1&sn=b250b40543a4f8c2c28827587dd62d02&chksm=cfe7a1c7f89028d118599648db1037bddaa7f0eefed08abb3e8fc10699c1421441c3517166bc&mpshare=1&scene=1&srcid=0117OKUhDuwgjxulTmbfCefn&sharer_sharetime=1673957661497&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2022-05-18 |
| 阿里淘系 | [深度粗排在天猫新品中的实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650462657&idx=1&sn=5e7ba268bb213b97e373c09ef8063234&chksm=839611d9b4e198cf0735bee5a88e32efbfdbaab402b6f5a74be1986304608f73bb87ecd72c23&scene=27#wechat_redirect) | 粗排 | 2022-05-18 |
| 阿里淘系 | [内容推荐场景中自监督学习的应用](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650462450&idx=1&sn=48c33f93cae32d6bf5ea6d8dfd0cb12b&chksm=839610eab4e199fcf614def6a660424a04196208d4acaf10ea653ca2920018f21226eb87cc42&scene=27#wechat_redirect) | 推荐 | 2022-05-17 |
| 阿里飞猪 | [主题与交互式推荐技术在飞猪个性化分发中的实践](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247501313&idx=1&sn=8f41c67db2b9fd8d016863c4bef7174f&chksm=a691b5ec91e63cfaaf84c2872a0a33f8736d5077711b5f10fdca7e2f5578b6a61d915a985f0a&scene=27#wechat_redirect) | 推荐 | 2022-05-16 |
| 美团 | [杨玉基：知识图谱在美团推荐场景中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247574417&idx=1&sn=87ba745e7e1180fc6f85349428a890e9&chksm=fbd611fdcca198eba7ba7f339556911ae27b4058e0ae27581f793280ac0fc34fbc4e49e4a23f&scene=27#wechat_redirect) | 推荐 | 2022-05-16 |
| 腾讯QQ浏览器 | [李晓亮：腾讯搜索词推荐算法探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247574304&idx=1&sn=142635ea47eb0bf24b4feaab967f6d04&chksm=fbd6114ccca1985aecefcc46ade6d4d878bc6109205c2b4f8d5802ef9a484aee4a2c12fffed7&scene=27#wechat_redirect) | 搜索 | 2022-05-15 |
| 京东 | [如何提升推荐系统的可解释性？京东智能推荐卖点技术全解析！](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247572115&idx=1&sn=e77ece68da5e843e620599cd9bc35ad9&chksm=fbd668ffcca1e1e90ee71c122a5c379051ef0ed6e9cb1460ffd8692c5066803524c6c4472480&scene=27#wechat_redirect) | 推荐 | 2022-05-07 |
| 阿里淘系 | [多任务学习模型ESMM原理与实现](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247571544&idx=2&sn=c298c717bb79092cb8ea7adf718cf64b&chksm=fbd66a34cca1e3222d5ab2f54185cea9732528721b3f0ad3df83dc15e14a30b1d6c6f64fafa2&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-05-06 |
| 华为 | [点击率预测模型Embedding层的学习和训练](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247570937&idx=1&sn=aa619fe9ca5ce9b655368d11bed4f42a&chksm=fbd66795cca1ee830ab6c13d90dcd0a465f4c0f1e871c207db97f588b228f8f9ad7feec48d96&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-05-04 |
| 阿里 | [序列特征在推荐算法中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247570552&idx=2&sn=6f5c88fc386de39080c8ab16ec415a28&chksm=fbd66614cca1ef02422ec1a182101aabfed8939a077d3825c9cc2efc2664364592ba949e59e3&scene=27#wechat_redirect) | 推荐 | 2022-04-28 |
| 网易 | [CIKM 2021 \| 云音乐提出与模型无关的冷启动推荐框架: MAIL](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247486194&idx=1&sn=48db3322795a4931f30c760017aaf9bc&chksm=ea2e7dd4dd59f4c2e568ddb5bd3a17fdf9c42701995b42d33252c0182341a1a909cf66be862d&mpshare=1&scene=1&srcid=0117Q0TI5TIkAQKoTGlkapeK&sharer_sharetime=1673958944207&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 冷启动 | 2022-04-27 |
| 阿里 | [深度解析开源推荐算法框架EasyRec的核心概念和优势](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247569807&idx=2&sn=8d133978b9c78529d6c83c756c4a242d&chksm=fbd663e3cca1eaf58e2fe5d7c88430ada4ffac92e7a96082906c03666d3fdc28548c59c1078f&scene=27#wechat_redirect) | 工程相关 | 2022-04-26 |
| 腾讯 | [腾讯邱东洋：深度模型推理加速的术与道](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247569443&idx=1&sn=c683867e850188217bcdce54b9243feb&chksm=fbd6624fcca1eb59366b793686f378217d677a394378e65bc5b24963d10fff77461618203f74&scene=27#wechat_redirect) | 工程相关 | 2022-04-22 |
| 阿里 | [杨旭东：冷启动推荐模型DropoutNet深度解析与改进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247569405&idx=2&sn=fb25b857a2355631e7236ad538b7db1a&chksm=fbd67d91cca1f48793667b8211a67d91087a206fddfe15cb3a81fca07a74db96dd206452cca7&scene=27#wechat_redirect) | 冷启动 | 2022-04-21 |
| 网易 | [从跨模态和上升通道谈富媒体内容的冷启动](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247485997&idx=1&sn=382ec987f91b1e9da9c9b99b4c26c927&chksm=ea2e7d0bdd59f41d9da9b6df7c4973eaab7a9d594cfd5250ca3128a9aaf7dee4a540485a616c&mpshare=1&scene=1&srcid=0117LxLqRhvnFtyKC08DdoKa&sharer_sharetime=1673958844890&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 冷启动 | 2022-04-20 |
| 阿里淘系 | [生成式重排在内容推荐中的应用实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650458750&idx=1&sn=263bc286f3bf0711380b4c15d746ecdc&chksm=83960266b4e18b702e68a2e6fc1537d412aae05c8679b2f93fd6cd8d9c2e15647af2decf2625&scene=27#wechat_redirect) | 重排 | 2022-04-19 |
| 阿里 | [刘童璇：阿里巴巴稀疏模型训练引擎DeepRec](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247569004&idx=1&sn=819194c1427369349458d65a4d372f4b&chksm=fbd67c00cca1f5165aa04c2a247b70ab435f3d38f95f3b737ee0613ef13da7d465e6cc3f72a4&scene=27#wechat_redirect) | 工程相关 | 2022-04-17 |
| 网易 | [冷启动算法系列-云音乐歌曲冷启动初探](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247485981&idx=1&sn=ca9f4b56e4225c26e1e477ad47e5ce71&chksm=ea2e7d3bdd59f42dfa7ed40277d8db305544f59fccdae53b81be9f6010a0ee94bc102e6172d5&mpshare=1&scene=1&srcid=0117vy6KkfZbqSewnRXKH9LX&sharer_sharetime=1673958897941&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 冷启动 | 2022-04-13 |
| 阿里淘系 | [商品序列建模在新用户承接上的应用实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650457465&idx=1&sn=0fab7290a4e7dc9e951da5c2fc6404f9&chksm=83960d61b4e18477d070f49f47f4dd27d6feae11e2b940439a5833d9c1d78fc629fb1f4811f1&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-04-06 |
| 阿里妈妈 | [阿里巴巴展示广告智能拍卖机制的演进之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247567877&idx=1&sn=1c8d1f781bd72fdf063f05694f8ff001&chksm=fbd67869cca1f17ff2d6a98f51c5b61792db7aeac74a8f1503155851e4f59e5dc69f0342f47f&scene=27#wechat_redirect) | 广告 | 2022-04-06 |
| 网易 | [5G+智能时代的多模搜索技术](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247567823&idx=2&sn=97cccbf605536b1b02b56485e6b6d3f2&chksm=fbd67ba3cca1f2b5fbae4f27941220e719144f7cb7fc1399c63d95c42d43ece6dbd649a6fcc1&scene=27#wechat_redirect) | 搜索 | 2022-04-05 |
| 腾讯音乐 | [QQ音乐推荐召回算法的探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247567741&idx=1&sn=6406f8181482a6be57eb0a752173fa1a&chksm=fbd67b11cca1f2076580fb3e08d635033bdb03fa7fd195f6b6e07d231d3c7b52b03f3fe02996&scene=27#wechat_redirect) | 召回 | 2022-04-03 |
| 网易 | [云音乐隐性关系链的探索与实践](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247485890&idx=1&sn=16486343e1cebcf9b77352826c5c307e&chksm=ea2e7ee4dd59f7f2559e53c5f174e1541f1b940257e8af9027416ebd38ea4e643c583d1a6a5e&mpshare=1&scene=1&srcid=01175jUTYWcRHTuTLYsLKiuB&sharer_sharetime=1673958857324&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 冷启动 | 2022-03-31 |
| 阿里淘系 | [淘宝逛逛召回算法实践总结](https://mp.weixin.qq.com/s/fN9s5Ml4GjGK2xLOeAUN4w) | 召回 | 2022-03-29 |
| 阿里淘系 | [Gradient Normalization在多任务学习中的优化实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650457145&idx=1&sn=569530d4129f0ba122b79ddd66e6e742&chksm=83960c21b4e18537aa1edaead0ecf40f1e74aec662f1bc69d8a166b55085862d16211aa661a6&scene=27#wechat_redirect) | 多目标&多任务 | 2022-03-29 |
| 美团 | [李翔：美团到店综合知识图谱的构建与应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247567452&idx=1&sn=4da4f736bb462d213f5c275181201f29&chksm=fbd67a30cca1f326d7e08bf37270fd446cd82d693b1054611a8f2e76bfdee328863eada422d4&scene=27#wechat_redirect) | 知识图谱 | 2022-03-28 |
| 哈啰出行 | [周冰倩：广告主视角下的信息流广告算法探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247567308&idx=1&sn=bf4cb94e1cf1ce58e01e5a9a1d9fabd1&chksm=fbd675a0cca1fcb643835a48add91625fda1f9dd22f6fde80e23310355ec144e93cb4f642e8c&scene=27#wechat_redirect) | 广告 | 2022-03-27 |
| 快手 | [王晓伟：图神经网络在快手推荐召回中的应用和挑战](http://mp.weixin.qq.com/s?__biz=Mzg2NzU4MDM0MQ==&mid=2247484777&idx=1&sn=8e258fae7c3c04d483dca1a74b5b6d46&chksm=ceb825b3f9cfaca56b9879bd8b621dd99ec89d5322a5cc17da49c76a629bce9c24c75a486155&mpshare=1&scene=1&srcid=0117cYykpg2l8QoQuZOe3Tvk&sharer_sharetime=1673959147851&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐&图网络 | 2022-03-23 |
| 阿里淘系 | [基于特征全埋点的精排ODL实践总结](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650455296&idx=1&sn=06621faf40213e4e56a3211a88a6e234&chksm=83967518b4e1fc0e38716b43f07fb863fa12b2f1ac1e8b2afb2ef0d062f091b3e375dde8f0f3&scene=27#wechat_redirect) | 工程相关 | 2022-03-22 |
| 小米 | [崔世起：小米小爱同学无效Query识别](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566960&idx=1&sn=e8cc6cc5f3a1f7de5eac0dee97debb6b&chksm=fbd6741ccca1fd0ad16036ace153dc09b06649e9235bc89f2eda09f87c1aeee9e713f073b6c0&scene=27#wechat_redirect) | 搜索 | 2022-03-20 |
| 腾讯音乐 | [QQ音乐推荐系统算法架构实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566913&idx=1&sn=2d203186459c22eb14d54745cecdd83e&chksm=fbd6742dcca1fd3ba5b947fa2914bef7b218e957c94b458a12824c0fd0802cb616051bbcad80&scene=27#wechat_redirect) | 推荐 | 2022-03-19 |
| 腾讯微信 | [微信全文搜索技术优化](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649769274&idx=1&sn=a46fc1574ecbf5cfddd1f40af9cb1b4f&chksm=beccd64189bb5f57f80799fd2ea51c7669942254a2223dea55fe7d2bfa5762410a784dec8e2f&scene=27#wechat_redirect) | 搜索 | 2022-03-14 |
| 京东 | [王冬月：京东推荐算法精排技术实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566783&idx=1&sn=7f693e5b57988166ec07017f32ff2b97&chksm=fbd677d3cca1fec550f381173c195aef54aab536ce429cb823d9c62c7ca2a66cde9eb09c30ca&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-03-14 |
| 网易 | [蒋能学：网易云音乐广告算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566714&idx=1&sn=fcccd4847149cb3496d10e2d4975c30a&chksm=fbd67716cca1fe00735a96213bcd8d208d15654acb63ce8fd1e0dc0c383d8352c89ced76327f&scene=27#wechat_redirect) | 广告 | 2022-03-12 |
| 美团 | [异构广告混排在美团到店业务的探索与实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651766855&idx=2&sn=3f501731584e8cdf6fa7d22fafc9d469&chksm=bd12190a8a65901cfbad1590c49044afdf81c4df281e23dab813c51acddbace87bf93a78202d&mpshare=1&scene=1&srcid=0117wolSN0KkwClWlrLhbYd9&sharer_sharetime=1673957140359&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 广告&混排 | 2022-03-10 |
| 阿里淘系 | [GNN在轻应用内容推荐中的召回实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650454966&idx=1&sn=a5721d265ed07138fdad3c8e1d06b727&chksm=839673aeb4e1fab8164ef508bfeddc4f4cfc2c76d8163cf209c871df94a0c3fb0b1fd7f9c9b6&scene=27#wechat_redirect) | 召回 | 2022-03-10 |
| 京东 | [张菡：深度学习下的京东搜索召回技术](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566529&idx=1&sn=aaedccdf162508b78b35b99b5262e47e&chksm=fbd676adcca1ffbbd669a3190c4b96561686716a2c03f813cbf71c5af8313e20eab654116c9c&scene=27#wechat_redirect) | 召回 | 2022-03-09 |
| 网易 | [实时增量学习在云音乐直播推荐系统中的实践](http://mp.weixin.qq.com/s?__biz=MzI1NTg3NzcwNQ==&mid=2247485614&idx=1&sn=07571004c063b7563fa83f0b38e4f9b0&chksm=ea2e7f88dd59f69e24c15d4cfee263f4dab871a8a5bc6a8ca798d76265497e418ff2c393229c&mpshare=1&scene=1&srcid=0117kMMwZFauG8GEMkGxRgkM&sharer_sharetime=1673958791203&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐&增量学习 | 2022-03-09 |
| 阿里淘系 | [超越I2I和向量内积，淘宝新一代召回范式：PDN模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566515&idx=2&sn=45d7744b256ca6a4f3871126e6c343a9&chksm=fbd676dfcca1ffc9008e4af615655bc243a502bef76ec9aa73cfa961f005a5ceddbf85135020&scene=27#wechat_redirect) | 召回 | 2022-03-08 |
| 虎牙 | [李茶：虎牙直播推荐系统架构详解](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247566074&idx=1&sn=8c6b37aa60324b26561a5d3fae6ae9b7&chksm=fbd67096cca1f98057c70929be491b04a58704d04ddf4896e77947b5927c62aea546610e1e73&scene=27#wechat_redirect) | 推荐 | 2022-03-02 |
| 阿里淘系 | [冷启动系统优化与内容潜力预估实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650453241&idx=1&sn=d30e011ac9e416aab54eb76378b43f39&chksm=83967ce1b4e1f5f79ce2067171d9c6336269edb47c88992ba765376438534ba13a6b83da287f&scene=27#wechat_redirect) | 冷启动 | 2022-03-01 |
| 哈啰出行 | [董彦燊：因果推断在哈啰出行的实践探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247565994&idx=1&sn=6d57d32a8d2d81d6540a5e0219d14528&chksm=fbd670c6cca1f9d034eb1a94314e838a09e843c65143995e0d133bc612596ba3817f73f99507&scene=27#wechat_redirect) | 因果推断 | 2022-02-28 |
| 贝壳 | [王志勇：贝壳CVR转化率预估模型实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247565976&idx=1&sn=a651d09cdd08268b1424c854790e3a59&chksm=fbd670f4cca1f9e25c39dea866a2b3c4ffeb954ad078e46404656f464f45eb4081307b8476cd&scene=27#wechat_redirect) | 精排&CXR预估 | 2022-02-26 |
| 京东 | [赵鑫：强化学习在京东广告序列推荐中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247565886&idx=1&sn=fbce6bf0053fc396ec28ef96b70b4549&chksm=fbd67052cca1f944934c670f15d55771cd9287962d642fb0ce39208d5bd769c35bd7692ab481&scene=27#wechat_redirect) | 广告 | 2022-02-24 |
| 阿里淘系 | [行为稀疏场景下的图模型实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650452759&idx=1&sn=9405ae3c91460fb6ad0e85389de5414c&chksm=83967b0fb4e1f219afa071fd46547c54a189ff468dcf9fd33ea6b6f9ae8fefcd2df7cf1007aa&scene=27#wechat_redirect) | 召回 | 2022-02-22 |
| 快手 | [赵炜琪：因果推断在快手推荐场景的应用探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247565718&idx=1&sn=5d5e7b94caa839ccf85e0b119de3ba64&chksm=fbd673facca1faecf357c3478bb5d0859c0e3a9f25110e8a1ba17a561b24ec8094ab07640988&scene=27#wechat_redirect) | 因果推断 | 2022-02-21 |
| 腾讯微信 | [微信强化学习推荐模型的知识蒸馏探索之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247565711&idx=2&sn=7f04ddc36909ebe7301775eda5fd577e&chksm=fbd673e3cca1faf50348726147937c20283f2b8c65f5f033852feeb2e9f7e4ed7c8d06c2190c&scene=27#wechat_redirect) | 推荐 | 2022-02-20 |
| 腾讯 | [一篇详文带你入门 Redis](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649768292&idx=1&sn=354dfe8a3186fd265dbe434738ef5599&chksm=beccd21f89bb5b093f7a7ee15b4ea54e0035b445f9835d5cd8835c8d4dd460a2303bdc2eb61a&scene=27#wechat_redirect) | 工程相关 | 2022-02-18 |
| 阿里飞猪 | [熊飞："猜你去哪"飞猪用户旅行意图预测](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247565613&idx=2&sn=f71fdb23b678e962f4cb9e4373d0f3c9&chksm=fbd67341cca1fa57fc35cbd6f260f27f9b058fe2d815aee5e0249b0f4e9c97e4e7a035460105&scene=27#wechat_redirect) | 搜索 | 2022-02-18 |
| 虾皮 | [下拉推荐在 Shopee Chatbot 中的探索和实践](http://mp.weixin.qq.com/s?__biz=MzkzMDE5MDgwMQ==&mid=2247486658&idx=1&sn=0ee241fe1d39ca49fa027df3157c2011&chksm=c27f487cf508c16a391b504cb12557a1e3b7b59e63c668f41b2956cddabd417d35d27a51b596&mpshare=1&scene=1&srcid=01178Hqxu4n7E06o8irFWJnX&sharer_sharetime=1673956927457&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2022-02-17 |
| 美团 | [美团搜索中查询改写技术的探索与实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651766615&idx=2&sn=89b1399f902ce8b01d2e5dc45c11ec43&chksm=bd12661a8a65ef0c8ac325db5450c1ce7e62dfeb87120569aca449afdbcc24a1e0a112eadbe6&mpshare=1&scene=1&srcid=0117flm3zao0X73AS87VEsRA&sharer_sharetime=1673957162379&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 搜索 | 2022-02-17 |
| 美图 | [多媒体内容理解在美图社区的应用实践](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247499655&idx=1&sn=0af7ce51790e7de995b989250af545ac&chksm=a6918c6a91e6057ca610820f4207531dd77de9541a534ab6df033691b21023d2c6a5d3736e70&scene=27#wechat_redirect) | 内容理解 | 2022-02-16 |
| 快手 | [将因果关系估计引入推荐系统、提升推荐模型效果，快手新研究被WWW22接收](http://mp.weixin.qq.com/s?__biz=Mzg2NzU4MDM0MQ==&mid=2247484702&idx=1&sn=33891737a46268a28d6676ca1e2e8212&chksm=ceb825c4f9cfacd2b0cb6ff6106940043d708260b561285cc7459a17bd65d3d16e3ddce95707&mpshare=1&scene=1&srcid=0117GxgZME41q4MyG15aaS66&sharer_sharetime=1673959171765&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 因果推断 | 2022-02-14 |
| 腾讯音乐 | [QQ音乐排序模型优化](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247564687&idx=1&sn=2825449485d6fae3ae2005c822ce8dc1&chksm=fbd64fe3cca1c6f5277e84d19e723e2ff4e165ced14d94d53bf93ce73878943ec9d7c0f005d3&scene=27#wechat_redirect) | 推荐 | 2022-02-14 |
| 58同城 | [苏永浩：Embedding技术在商业搜索与推荐场景的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562574&idx=1&sn=2c5c787485131673da963e4a1ca8610a&chksm=fbd64722cca1ce34155e3c4507bea25b4debca0c0cbcb88871bcc3f6637efa4c7452d24ec092&scene=27#wechat_redirect) | 召回 | 2022-02-11 |
| 快手 | [渠江涛：重排序在快手短视频推荐系统中的演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562529&idx=1&sn=6bae7191d8f711d68c1520f4e8a28c7a&chksm=fbd6474dcca1ce5b112eb645ff15d173c7054d2343b16e4d3674201c4481314fa9297b90b0b7&scene=27#wechat_redirect) | 重排 | 2022-02-10 |
| 快手 | [李翱：因果学习在用户增长中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562443&idx=1&sn=e648c2b1fcd04c94fe39c74176b5d5d5&chksm=fbd646a7cca1cfb135acbd3ee5e460e846dd7851c24f5b8ed2b30556d967f5ad2ae54862f6b7&scene=27#wechat_redirect) | 因果推断 | 2022-02-07 |
| 58同城 | [刘德华：标签推荐与“猜你想找”算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562403&idx=1&sn=b639f10eabbc85c33cb47773f6e7f927&chksm=fbd646cfcca1cfd94d90c73d665d9a056bf90e40b8c9857d5f5476f6ae8f1eb41fff5302508f&scene=27#wechat_redirect) | 推荐 | 2022-02-05 |
| 腾讯音乐 | [腾讯音乐知识图谱搜索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562398&idx=1&sn=a4a75e80defd853797980fc99a09b6b3&chksm=fbd646f2cca1cfe4fab6870c681e40db76cd1b0bebdd55f93034ed812ac1ac1f38908a2a6d59&scene=27#wechat_redirect) | 搜索 | 2022-02-04 |
| 一点资讯 | [郭沛东：图模型在信息流推荐的原理和实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562297&idx=1&sn=38d236570827c2d8422dbfe1fbc93819&chksm=fbd64655cca1cf43815128dc9a8b7adf5efe1d6779fa7feb60ad9f1414767cf57623cbbd41f1&scene=27#wechat_redirect) | 推荐&图网络 | 2022-01-28 |
| 阿里淘系 | [推荐场景下融合多模态信息的内容召回模型](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650451312&idx=1&sn=a9bf674c661cb9f4ea5b9a1a86b874ac&chksm=83966568b4e1ec7eb52f139edd3ede3df3fb6b23f4a4951be6b66db1390264b58e4a5ee43329&scene=27#wechat_redirect) | 召回 | 2022-01-26 |
| 阿里淘系 | [多序列融合召回在新用户冷启动上的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247562067&idx=2&sn=9a47510cfb928f3d0001428f3a1f7555&chksm=fbd6413fcca1c829d11e66edf61b8cfa7b0b735ac3425fb3f67cfdfb041f9dbc5d247f06391b&scene=27#wechat_redirect) | 召回 | 2022-01-23 |
| 阿里淘系 | [ZEUS：淘宝多场景推荐排序模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247561697&idx=2&sn=9db06881ce75388999f96276289f2bf2&chksm=fbd6438dcca1ca9b4c7c1f40224c735499a6bacc952640d4a1f3cb1233d3a5e2b53c2ec983aa&scene=27#wechat_redirect) | 推荐 | 2022-01-19 |
| 贝壳 | [周玉驰：因果分析在贝壳的探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247561513&idx=1&sn=5b818890be25a6b346041bcd45f9b5c7&chksm=fbd64345cca1ca5395f1cd95f1cc0d0f9b4bcbd330f26e2fea657424bde76bd74b57bf989720&scene=27#wechat_redirect) | 因果推断 | 2022-01-17 |
| 腾讯音乐 | [腾讯音乐多模态音乐匹配技术与应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247561463&idx=1&sn=264c42e7c9207cd57e0f13937985a869&chksm=fbd6429bcca1cb8d461a43081195f95972c08d8055680d0b7fed174734abf042162f673d0913&scene=27#wechat_redirect) | 搜索 | 2022-01-15 |
| 阿里淘系 | [大淘宝技术“搜索算法”专场①：淘宝搜索召回、个性化搜索排序](https://www.bilibili.com/video/BV1QS4y1j7yK) | 搜索 | 2022-01-14 |
| 阿里淘系 | [大淘宝技术“搜索算法”专场②：电商搜索相关性、电商知识图谱](https://www.bilibili.com/video/BV1GY411h7MH) | 搜索 | 2022-01-14 |
| 阿里淘系 | [直播预告 \| 1月13日下午，“搜索算法”专场②：电商搜索相关性、电商知识图谱](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650450365&idx=2&sn=cac748e80be91c0ef674b0f5cffd8892&chksm=839661a5b4e1e8b39164b66b6d3c34f673353b623f8e77d8588488696992dad60f205192d56a&scene=27#wechat_redirect) | 搜索 | 2022-01-12 |
| 阿里淘系 | [直播预告 \| 1月12日下午，“搜索算法”专场①：淘宝搜索召回、个性化搜索排序](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650450321&idx=2&sn=f80e1432c9d601cdead700c4a2f4c9c6&chksm=83966189b4e1e89fff4e286b3543aaa4caa1a897bcd65f49754d6a35735e04299cac329102a2&scene=27#wechat_redirect) | 搜素 | 2022-01-11 |
| 阿里淘系 | [7种经典推荐算法模型的应用](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650447143&idx=1&sn=28572b3214b41042573190f918fec5e2&chksm=8396553fb4e1dc299959b25ebba018de65a0ad01f764cff9be3691be7a28efe20bc494af76a0&scene=27#wechat_redirect) | 推荐 | 2021-12-30 |
| 京东 | [赵学敏：京东商品图谱构建与实体对齐](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247560198&idx=1&sn=d6245b5ad0e0a45828d8a5a3d42565b3&chksm=fbd65e6acca1d77c4219211313cf049d7c3b3f1380137f4a4057180e3453ac286cc90489f3a2&scene=27#wechat_redirect) | 知识图谱 | 2021-12-29 |
| 网易 | [网易云音乐广告CTR预估模型演进过程](https://zhuanlan.zhihu.com/p/448175622?utm_medium=social&utm_oi=32492828491776&utm_psn=1598782592987373568&utm_source=wechat_session) | 精排&CXR预估 | 2021-12-21 |
| 阿里淘系 | [多序列融合召回在新用户冷启动上的应用](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650445597&idx=1&sn=3cf659eb6888d315eef88a40ca01b35e&chksm=83965f05b4e1d613ae13a009563d6ddd5cefe111249309968461b388dba2b9fceb6c059014f9&scene=27#wechat_redirect) | 冷启动 | 2021-12-21 |
| 阿里淘系 | [大淘宝技术“推荐算法”PART 1](https://www.bilibili.com/video/BV1QP4y1n7vD) | 推荐 | 2021-12-20 |
| 阿里淘系 | [大淘宝技术“推荐算法”PART 2](https://www.bilibili.com/video/BV1CL411j7sP) | 推荐 | 2021-12-20 |
| 阿里淘系 | [大淘宝技术“推荐算法”PART 3](https://www.bilibili.com/video/BV1Bg411w7ib) | 推荐 | 2021-12-20 |
| 58同城 | [沈冰阳：强化学习在推荐冷启动优化中的实践探索！](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247559222&idx=1&sn=9bd74ce22471f24c67ede5664e3d52ca&chksm=fbd65a5acca1d34c479c885f71f9c936be3dcacdf07a6b93804497ce2a80e6e1dbbd6c2ccb01&scene=27#wechat_redirect) | 冷启动 | 2021-12-17 |
| 阿里淘系 | [内容推荐场景下多模态语义召回的若干实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650445349&idx=1&sn=bb8ad24cef7f34bd46fe35d0cb370958&chksm=83965e3db4e1d72ba530d9f06acaa2d0432338935e9585e530958dba2d42f20971047b0b0c78&scene=27#wechat_redirect) | 召回 | 2021-12-14 |
| 阿里淘系 | [深度粗排模型的GMV优化实践：基于全空间-子空间联合建模的蒸馏校准模型](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650445139&idx=1&sn=c43febc0a43bf5b4165d06cceffd873c&chksm=83965d4bb4e1d45d50fd46a3776bf9ebfe78477c45a872aba220ff37aa331fda2fe07874c803&scene=27#wechat_redirect) | 粗排 | 2021-12-13 |
| 阿里淘系 | [阿里新一代召回技术：从TDM到二向箔的新突破！](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247558984&idx=1&sn=b43d63234470d398222d969bd832ceb4&chksm=fbd65524cca1dc3237395c3d5971388533d363d8d8ea0ac15ab7ae1fe1f976e04b35abe4a17a&scene=27#wechat_redirect) | 召回 | 2021-12-13 |
| 58同城 | [祝凯文：推荐算法在商业化场景中的探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247558876&idx=2&sn=9661f9e62d675dc9c6c1e1755166f475&chksm=fbd654b0cca1dda662a444099587fb756253ff670453f1093fbdab68caffd9ce31c3864a86c6&scene=27#wechat_redirect) | 推荐 | 2021-12-12 |
| 阿里淘系 | [2021召回技术在内容推荐的实践总结](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650443071&idx=1&sn=b61d6b1fdcf0c61bccb3988dd2516616&chksm=83964527b4e1cc31a67ced58e4a1559d8214f5a560258aaac51223c393ec829d3d2ede1faadb&scene=27#wechat_redirect) | 召回 | 2021-11-30 |
| 阿里淘系 | [阿里淘系技术：算法黑科技](https://www.bilibili.com/video/BV16M4y1P71Y) | 搜索 | 2021-11-29 |
| 快手 | [「繁星」：快手搜索在向量检索方向的探索和实践](http://mp.weixin.qq.com/s?__biz=Mzg2NzU4MDM0MQ==&mid=2247484410&idx=1&sn=6eb90265ecadfd8a6239142e82d2791e&chksm=ceb82320f9cfaa3605c0808a6cc59e1272e4bd66966707bfea69c443bf6f94e7f084d0fb68d0&mpshare=1&scene=1&srcid=0117gma2C2J5yABFspK8xOMO&sharer_sharetime=1673959158573&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 召回 | 2021-11-29 |
| 腾讯音乐 | [QQ音乐推荐系统的精细化调控](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247557961&idx=2&sn=cfaf7721b9c7892654fb6d22fc3dcb9a&chksm=fbd65125cca1d83361018b1cb258acf75919d79989f306bb031eb61a86aa60e38423ce26b7a3&scene=27#wechat_redirect) | 推荐 | 2021-11-28 |
| 阿里淘系 | [GNN在下拉推荐的应用](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650442614&idx=1&sn=9f70b34865023eb21948da0e1048caa8&chksm=8396436eb4e1ca7838bee45c86575fd55a5ab4890d00ab39c8a79f9d7152a19ed7c173139ebe&scene=27#wechat_redirect) | 推荐 | 2021-11-24 |
| 美团 | [美团搜索多业务商品排序探索与实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651765674&idx=1&sn=55f3a13f9b2ecc1b0c28a76e76b35727&chksm=bd1262e78a65ebf12783a6b593cef4f8fe0a5b1f41eac019ce707ff01cc9c307e6febcefc634&mpshare=1&scene=1&srcid=0117VHqucNGNj19mtFAk5cYg&sharer_sharetime=1673957152451&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 搜索 | 2021-11-18 |
| 阿里飞猪 | [阿里飞猪林睿：从核心因子预估>实体识别，如何实现文本和空间的搜索相关性？](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247557338&idx=2&sn=ab7ae767a2504d9cde93552d35d402fd&chksm=fbd652b6cca1dba0bac36a18cd430d38d30d76f1f9112bde9fc42e8c723eb4a3a71c50fdcafa&scene=27#wechat_redirect) | 搜索相关性 | 2021-11-16 |
| 字节跳动 | [字节跳动高伟豪：训练目标不一致？损失无法学习？深度召回解难题！](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247556442&idx=1&sn=61144058d5ac801109ca343d4480295d&chksm=fbd7af36cca02620de8ad397ef047fc8f1dfc896c6a44c935e79f19eccea6194e471f6252283&scene=27#wechat_redirect) | 召回 | 2021-11-10 |
| 美团 | [美团王庆：当老板对指标进行灵魂拷问时，该如何诊断分析？](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247555956&idx=1&sn=9495f84c782e741e7609b5e0ba8b9833&chksm=fbd7a918cca0200eb0d1aba6a17889b91b0235df7edc6e5b4c611aabc464357d445f2c6ee132&scene=27#wechat_redirect) | 其他 | 2021-11-04 |
| 京东 | [京东李欣如：从单目标排序到多目标模型，显著提升多业务效果！](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247555887&idx=1&sn=72e77940abd250906cf42e03c8027c18&chksm=fbd7a943cca020551709b8e89bfc1c5c494fae68beb2d87d14cbea17f83455524443539469f6&scene=27#wechat_redirect) | 多目标&多任务 | 2021-11-02 |
| 百度 | [基于用户出行意图建模的百度异地POI推荐](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247555532&idx=1&sn=df29d507d23d2431687d85b3ac865763&chksm=fbd7aba0cca022b615356a849cc9b60c32e0461d8d50328f5024408e0a4acda5ecb688600234&scene=27#wechat_redirect) | 推荐 | 2021-10-29 |
| 阿里飞猪 | [阿里飞猪推荐算法探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247554796&idx=1&sn=e96ad50dfbf4e2b54cfff9ee3ee122b7&chksm=fbd7a480cca02d96c66772353c5e4b54fc80d2577775337a53b6d916e753c2cf08af9d858be3&scene=27#wechat_redirect) | 推荐 | 2021-10-21 |
| 腾讯 | [一文搞懂CTR建模](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649765103&idx=1&sn=7da591618dfacca5314f77634861bd1e&chksm=becca79489bb2e82f1d4bb047b759a75c98257980e09514ebf83f72177a5aafec7945e340f8c&scene=27#wechat_redirect) | 精排&CXR预估 | 2021-10-18 |
| 58同城 | [多目标排序在58同城房源推荐中的实践探索](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247496575&idx=1&sn=ea69970e5ce1e56683c0dfb5491e4c63&chksm=a691809291e60984f7e09ea5912be01f732fad486f8c1439152d6744b745c0989c8a5a38c713&scene=27#wechat_redirect) | 多目标&多任务 | 2021-10-18 |
| 蜻蜓FM | [蜻蜓FM实时推荐系统的发展和演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247554470&idx=1&sn=2ff40b9e09a4424c850059053a065178&chksm=fbd7a7cacca02edca60d87ea1be7ec4ec489d1688a67e4451e8c8cb42f8d4da0027cbc4abe8e&scene=27#wechat_redirect) | 推荐 | 2021-10-14 |
| 美团 | [广告深度预估技术在美团到店场景下的突破与畅想](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651765021&idx=1&sn=3ac05ac64f650bcedd4f75d5aa715771&chksm=bd1260508a65e9462f356aab0fc0df37e4860628f3f404db9099b8195991bfd9a4542c35dd80&mpshare=1&scene=1&srcid=0117FB6mPZqwGWEVytjcUxEH&sharer_sharetime=1673957236741&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 精排&CXR预估 | 2021-10-14 |
| 阿里妈妈 | [阿里广告技术新突破：面向最终目标的全链路一致性建模](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247554157&idx=1&sn=cec38d80b7d75845c6af5bca7bf9087b&chksm=fbd7a601cca02f17ff5c1c5baee827ca106761579fdacc03e082e8034978a4860bf7d4c63dc3&scene=27#wechat_redirect) | 广告 | 2021-10-11 |
| 58同城 | [广义多目标算法探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247553674&idx=1&sn=93fd72425a2e1fc8a1aaaa48075a7f09&chksm=fbd7a0e6cca029f099db1ee7f6d44e0bc32ad91f21d661573be58e8e2d323aa822c37fa0219d&scene=27#wechat_redirect) | 多目标&多任务 | 2021-10-04 |
| 58同城 | [多目标排序在二手房推荐系统的实践探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247551834&idx=2&sn=98052911088d340991cec0c6c804f389&chksm=fbd7b936cca03020aaae4b4c5820e678017589affa19dedfe4fea56059c10c6922380ea65a6c&scene=27#wechat_redirect) | 多目标&多任务 | 2021-09-19 |
| 阿里淘系 | [淘宝直播全屏页重排算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247550322&idx=2&sn=5f46d888ca18541b9b3d9929cdbb369f&chksm=fbd7b71ecca03e089c2a6c7996fef0b640af5f8ea79c000418847847e69276d07035bc483370&scene=27#wechat_redirect) | 重排 | 2021-09-04 |
| 阿里妈妈 | [阿里妈妈广告创意优选](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247549101&idx=2&sn=08fab37f73d47f7215e0a5f8fd1ad24c&chksm=fbd7b2c1cca03bd716dcd437fabd34bdf9fb802dbef59e18039dede88511ff113864352b1172&scene=27#wechat_redirect) | 广告 | 2021-08-27 |
| 阿里淘系 | [SIGKDD2021 \| 淘宝搜索向量化召回实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650433549&idx=1&sn=7e352d215146a445ea47a566a4aa8411&chksm=8396a015b4e12903e30ea108bb8fd4c963d4b0af6bd691a869ec77220211427084a60ce57cf1&scene=27#wechat_redirect) | 召回 | 2021-08-25 |
| 腾讯微信 | [微信看一看如何过滤广告文章？](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247547626&idx=2&sn=3954ffc136544fd683b1629c9df8a978&chksm=fbd78886cca0019084a7b35ed0fa21e5f753a22d172c4b63dbe756d2b5581242fdf8c7280fe8&scene=27#wechat_redirect) | 广告 | 2021-08-14 |
| 阿里妈妈 | [朱小强｜屠龙少年与龙：漫谈深度学习驱动的广告推荐技术发展周期](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247547435&idx=1&sn=d629f799eb85ac8e90c6962cd424d7ee&chksm=fbd78847cca00151fdd192d1152aaae4cc7ec1b7a1a67487f4e5619070475020b8fc0fb83de1&scene=27#wechat_redirect) | 广告 | 2021-08-10 |
| 阿里淘系 | [淘宝视频的跨模态检索](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650433132&idx=1&sn=d3d9df3adbb8533eaa2f60f80dd8fc2f&chksm=8396ae74b4e12762ac17b45a41e0e4b98d2cb3493eb6e44b0e338d3b594f685efa43bff5a4ce&scene=27#wechat_redirect) | 搜索 | 2021-08-09 |
| 阿里妈妈 | [阿里妈妈展示广告预估校准技术演进之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247547345&idx=1&sn=343a931f247a2ebc0e53b40298b0bb17&chksm=fbd78bbdcca002abce76f5c4bf6aca9d44e45bf9e16ee219ac33620521b9e2c81186c1933ad8&scene=27#wechat_redirect) | 广告 | 2021-08-09 |
| 京东 | [多类目MoE模型在京东电商搜索中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247547245&idx=1&sn=e5d4731f4b0b665057786318c6fac68c&chksm=fbd78b01cca00217b66667d41cdbee41ebce14a58d8c9f99ce48838ffd4713560e78919e6ede&scene=27#wechat_redirect) | 搜索 | 2021-08-07 |
| 阿里淘系 | [淘宝视频内容标签的结构化分析和管理](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650433059&idx=1&sn=7282fc6987a94b5d32d88ffc513dcc15&chksm=8396ae3bb4e1272d3cc9a73ce8b2cd7aa6914c80958e57b13bcdba379fdbe755ac7d304547f3&scene=27#wechat_redirect) | 内容理解 | 2021-08-06 |
| 微拍堂 | [深度召回在文玩个性化推荐中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247547145&idx=1&sn=de1b92402bf93a5777ab0e7faac3dd57&chksm=fbd78b65cca0027348e33d8be4c044b190a25129cbd12cad5dedef08f90c87e42796a1fd14f5&scene=27#wechat_redirect) | 召回 | 2021-08-04 |
| 阿里妈妈 | [FAE：阿里广告归因分析与用户增长分析引擎](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247547084&idx=1&sn=7bcfbba74623c84bcc850bd042c279b6&chksm=fbd78aa0cca003b6726344ce152f7ddcb1fae15932c262c042b43783260b1b7b69ce15524cdc&scene=27#wechat_redirect) | 广告 | 2021-08-03 |
| 美团 | [美团商品知识图谱的构建及应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247546914&idx=1&sn=b553a4d0cb60b9220b967970f9b54b13&chksm=fbd78a4ecca00358b84bd7d41eda415ea50169fe7b23bb27009bc526ccabe7dd9cdbf1707411&scene=27#wechat_redirect) | 知识图谱 | 2021-07-31 |
| 阿里 | [阿里1688直播推荐算法实践](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247495242&idx=1&sn=c739912e3f2116eb000255ae368b3c07&chksm=a6919da791e614b17afc52b99157ac735a66990946b42ca9ae437f96c112f8cd08d4cbfca128&scene=27#wechat_redirect) | 推荐 | 2021-07-28 |
| 阿里淘系 | [2021年，算法工程师必备的能力是什么？](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650432692&idx=1&sn=db725557ba260b82ca2601d578687916&chksm=8396acacb4e125baa2f9fb61e7b30015e9bfaf7cc327734ce6193e0e6378dcc9637486eb6935&scene=27#wechat_redirect) | 其他 | 2021-07-26 |
| 阿里淘系 | [淘宝详情页分发推荐算法总结：用户即时兴趣强化](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247546474&idx=2&sn=ada65eaa15c7beef9c2f70f586d8dfbf&chksm=fbd78406cca00d10b2532ffe6c937ef216cfa96c90efaf91901233d8dbd1be11aa396a5bfafd&scene=27#wechat_redirect) | 推荐 | 2021-07-24 |
| 阿里妈妈 | [阿里妈妈流量反作弊算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247546358&idx=2&sn=b8b5605be6321a2e3291733aafc45053&chksm=fbd7879acca00e8c8f1891dbc01322991153e72a45a7b468a2c5a160acb1300ecc44843be1cf&scene=27#wechat_redirect) | 广告 | 2021-07-23 |
| 58同城 | [58同城CRM多目标排序算法](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247545833&idx=1&sn=9feb4b0a4b6ab469a434df7696efaadd&chksm=fbd78185cca00893a23e1a61d49c0d5e86e291450a1d8444c171fbd0a07d9365ae358d021175&scene=27#wechat_redirect) | 多目标&多任务 | 2021-07-17 |
| 阿里妈妈 | [阿里妈妈在线分流 AB Test](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247545777&idx=2&sn=bf9ee1e9d70148449f0643532fca9db6&chksm=fbd781ddcca008cbbec49ba2d0a31fd36f7390828ac5e9ebce831a2a787d29f18cdd38c93732&scene=27#wechat_redirect) | 数据科学 | 2021-07-16 |
| 腾讯音乐 | [全民K歌直播推荐算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247545585&idx=1&sn=d45b4e3909c2f1677d9900d8f07718a1&chksm=fbd7809dcca0098b70f8213ac4c86badf8921cc680a462d98fd52ee3a84f5d2ffb23187a49ec&scene=27#wechat_redirect) | 推荐 | 2021-07-12 |
| 美团 | [多业务建模在美团搜索排序的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247545317&idx=2&sn=acbd7df8a7554d92cb086febf4f3c0bd&chksm=fbd78389cca00a9f3fd3d3bbca7b61447c82566a5185db052cbac8241adc1164bc81685e2701&scene=27#wechat_redirect) | 搜索 | 2021-07-10 |
| 丁香园 | [丁香园基于Milvus的向量召回应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247544207&idx=2&sn=4adac4d8c43122374905f236634e2b0e&chksm=fbd79fe3cca016f5f2896aa33cebd1442569f73aa8c807d4c0a0ac8753898e42fa736552bf1d&scene=27#wechat_redirect) | 召回 | 2021-07-02 |
| 美团 | [美团外卖美食知识图谱的迭代及应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247543721&idx=2&sn=c4a4a98515f9f33be4b505977acb4499&chksm=fbd799c5cca010d3f62d23492016a42221f2cad319507541e6ce52a6d4c41bd19608ab267979&scene=27#wechat_redirect) | 知识图谱 | 2021-06-20 |
| 阿里飞猪 | [拼接召回在飞猪交通域的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247543682&idx=1&sn=49bb76a0dd3eb1263a1e5e204c95857e&chksm=fbd799eecca010f8fd2ec7376d7b304f6bf88c7dee9cd7305c9c9bcf7fdc3e6bc3ad22184207&scene=27#wechat_redirect) | 召回 | 2021-06-18 |
| 腾讯微信 | [针对多目标推荐任务，微信看一看用PAPERec框架逼近帕累托最优](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247543460&idx=2&sn=833b99ad67ff1914b94453aaa1e752c8&chksm=fbd798c8cca011de8743b244e2a39159e26691a963d6a046280b6dbdd6bd7e6f38ae4df53e33&scene=27#wechat_redirect) | 多目标&多任务 | 2021-06-15 |
| 阿里妈妈 | [阿里妈妈搜索广告CTR模型的“瘦身”之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247543441&idx=2&sn=2d283f1e03d1731d8a06a8f7b2115872&chksm=fbd798fdcca011eb3135738e25b4aef91b2a7305641c2ae505268a01e665014c1a77fe30583a&scene=27#wechat_redirect) | 精排&CXR预估 | 2021-06-14 |
| 腾讯微信 | [用于看一看list-wise推荐系统的HRL-Rec模型简述 \| AAAI-2021](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247543407&idx=2&sn=5ef8d7ada9e6060d0f88c303602b3db5&chksm=fbd79803cca01115ac9ea59e34afb653d3d9f1f7fd2857f77d6252cd0cd62aa1f47d7434a93e&scene=27#wechat_redirect) | 推荐 | 2021-06-13 |
| 阿里淘系 | [工业界常用的推荐系统模型有哪些？](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650431219&idx=1&sn=0b66e25d6693363d34cafbb6abc72fa8&chksm=839696ebb4e11ffd2dc45c654d5e6b254625719b6a4e01ce4186218c3f147dd3dd5398590680&scene=27#wechat_redirect) | 推荐 | 2021-06-07 |
| 京东 | [大规模图算法在京东广告的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247542308&idx=1&sn=822ad9c80b39f9fd281573f2deb610ac&chksm=fbd79448cca01d5e9697b7a943cb550483685ddfe10222abf4612aa29007481d35b11a461b85&scene=27#wechat_redirect) | 广告 | 2021-06-02 |
| 阿里妈妈 | [阿里妈妈搜索广告CTR模型演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247542213&idx=2&sn=d0708ac37e8805c8ff385600bc3888e1&chksm=fbd797a9cca01ebfccee12ef66cf7b9dc19753e960dbf1de254520c050e7131740b382f34ac8&scene=27#wechat_redirect) | 精排&CXR预估 | 2021-06-01 |
| 阿里飞猪 | [阿里飞猪个性化搜索排序探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247542183&idx=1&sn=4f844163c99f7ee554554b4be1e31512&chksm=fbd797cbcca01edde5bd80a9ab67ff22a250ab98d473694105a83b9ae242f8867fcbf11a4d38&scene=27#wechat_redirect) | 搜索 | 2021-05-31 |
| 阿里淘系 | [5大经典排序算法在淘宝“有好货”场景的实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650430647&idx=1&sn=de550537683d9444813a16703d60780e&chksm=839694afb4e11db952c355a6b1f6f9bad00e713de7a5f9bbe847a5dbc0cddd4cabc3c604ca47&scene=27#wechat_redirect) | 推荐 | 2021-05-28 |
| 蜻蜓FM | [蜻蜓FM信息流推荐探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247541942&idx=1&sn=60eeeb4a69f817d2cff29750f8b7fbdb&chksm=fbd796dacca01fcc8ff53c481fb219368b24b48b4e44c068f588b9d1921742ef973663cf23c6&scene=27#wechat_redirect) | 推荐 | 2021-05-26 |
| 阿里淘系 | [分钟级在线深度学习在手淘信息流排序模型中的探索与实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650430600&idx=1&sn=313876949aa19b5d38e4f9363abf7b27&chksm=83969490b4e11d86ca19aea8c1e9034577051dac13f5ce04a3e241b3732dbc75d65f35cc1be2&scene=27#wechat_redirect) | 推荐 | 2021-05-26 |
| 腾讯微信 | [微信视频号推荐算法挑战赛baseline分享](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247494303&idx=1&sn=b1d8d66bd590e66158b5ce745f2dc6ea&chksm=a691997291e610645cd6962a33c83945ddbc42a1630ac48bbef53bad9f22239a6db81a20a7cd&scene=27#wechat_redirect) | 推荐 | 2021-05-23 |
| 阿里妈妈 | [你真的懂点击率（CTR）建模吗？](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247541722&idx=2&sn=828032935a3f384d75fbc54a1396cf12&chksm=fbd791b6cca018a021c5e53221b684aba588f03176e3b9cc2b839b6820f8c8766b79a074e4fc&scene=27#wechat_redirect) | 精排&CXR预估 | 2021-05-20 |
| 阿里飞猪 | [因果推断在阿里飞猪广告算法中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247541692&idx=1&sn=478e62d4865aa51a84f1d89ef0d862c0&chksm=fbd791d0cca018c6e5445ee84e6bccfc698d72d68e23e8b989ce3ff428c722ce019254ad6281&scene=27#wechat_redirect) | 因果推断 | 2021-05-19 |
| 爱奇艺 | [爱奇艺短视频推荐：多兴趣召回篇](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247541265&idx=1&sn=5446849bfdf0f0ce571e5eac412dd04b&chksm=fbd7907dcca0196bb199142242773bf89fb3393c6a9e594a8ecead15ef20b86d2456faa05280&scene=27#wechat_redirect) | 召回 | 2021-05-15 |
| 滴滴 | [滴滴连续因果森林模型的构造与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247541235&idx=2&sn=eeb61de139b90caa87add3aacf39ed29&chksm=fbd7939fcca01a89391bc124f54ccf8e58baca2b597b54b39ba3c9dbd3c5b9bdac6e5fb6809f&scene=27#wechat_redirect) | 因果推断 | 2021-05-13 |
| 美团 | [Query理解在美团搜索中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247541036&idx=1&sn=136c52347a6e6fde29d9f7604df4d0e8&chksm=fbd79340cca01a5618af600e66f2dd392cdd0fe8615cacf3d20ec55e0167a7108dfd6c0859f1&scene=27#wechat_redirect) | 搜索 | 2021-05-07 |
| 阿里淘系 | [MIND - 基于动态路由的用户多向量召回](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650428919&idx=1&sn=2a687d967536d65d31f026243b74479a&chksm=83969defb4e114f9ecf975a4b55836e0be86748cd76cc1cf3e3e2db6344478925c4c454ace32&scene=27#wechat_redirect) | 召回 | 2021-04-26 |
| 阿里淘系 | [SIGIR2021 \| 超越I2I和向量内积，淘宝新一代召回范式：PDN模型](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650428918&idx=1&sn=3d1b828d0bc685a357a13a607cad365c&chksm=83969deeb4e114f81484cb3c0216c0a6cdf55ae2d6dc824963fd7ee2cb2b09978a906aabda1c&scene=27#wechat_redirect) | 召回 | 2021-04-25 |
| 阿里妈妈 | [阿里定向广告智能投放技术体系](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247540489&idx=1&sn=56258f5ebcff70e17e6d026aba8fd059&chksm=fbd7ed65cca06473cd2ff831b68672ec1b19f43b993c6bcd8d7fd5c3bfbffe6898f2a6a79855&scene=27#wechat_redirect) | 广告 | 2021-04-24 |
| 阿里淘系 | [没什么是一次排序解决不了的，如果有，那就One more time](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247539967&idx=2&sn=6c386bbb663d5c15432c4b319e7cab15&chksm=fbd7ee93cca06785618c0a96e69fb9ec45af73e9a1bcfa4cf03e33c2e14b81409702676b878e&scene=27#wechat_redirect) | 推荐 | 2021-04-17 |
| 腾讯看点 | [腾讯 QQ 看点图文多目标推荐实践经验](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649757741&idx=1&sn=b77ae57ee2c7ab4c9621ec4cfbca1a85&chksm=becc8b5689bb0240959c0bbd40a104f0646b235f09e89cf20a01099d9d4bdc8843bd499f3d8c&scene=27#wechat_redirect) | 多目标&多任务 | 2021-04-09 |
| 腾讯微信 | [微信看一看实时相关推荐介绍](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649757740&idx=1&sn=51e5809fcf1b2f148dfd284d4628c57a&chksm=becc8b5789bb0241136a70f726c94007f8b61d62bc87a6d4f09ca8d8d80eff5382c735fae685&scene=27#wechat_redirect) | 推荐 | 2021-04-08 |
| 腾讯音乐 | [全民K歌推荐后台架构](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247538234&idx=1&sn=8626d27fd350c9f3008fdb5944cfb608&chksm=fbd7e456cca06d40a769a4241877a3beb494e94a6a548687ca3b449510a7320f26d30db979ab&scene=27#wechat_redirect) | 工程相关 | 2021-04-02 |
| 腾讯音乐 | [全民K歌内容挖掘与召回](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247537974&idx=1&sn=116f1bcaa683ea35587b0483d9599d4d&chksm=fbd7e75acca06e4c560519cac81cb324be3737b524beca1a249ac114dbfa99109e1fb71361f7&scene=27#wechat_redirect) | 召回 | 2021-04-01 |
| 陌陌 | [模型化召回在陌陌社交推荐的应用和探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247536974&idx=1&sn=77201e9ee0390fa0652424e67e6b2b2e&chksm=fbd7e322cca06a34698caf1c601871fcfd3e39f19e947fc871fb57760fc6d8f9f00c0e5e9c8b&scene=27#wechat_redirect) | 召回 | 2021-03-20 |
| 阿里淘系 | [超长用户行为建模在躺平家居内容推荐中的应用实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650423941&idx=1&sn=de554547923b2a5bed291727600c6756&chksm=83968a9db4e1038ba8f117a02555969fd1d5c8999c988219a64de43ab300ca838ead9520ab73&scene=27#wechat_redirect) | 推荐 | 2021-03-18 |
| 阿里淘系 | [深度排序模型在淘宝直播的演进与应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247536094&idx=1&sn=b5fa05a617b40d0af80f5d2c13933e26&chksm=fbd7ffb2cca076a4139ee592d1bc6884cc3e778f588c89048ebbe0ac1b07f3e659013e230842&scene=27#wechat_redirect) | 推荐 | 2021-03-17 |
| 腾讯音乐 | [腾讯音乐：全民K歌推荐系统架构及粗排设计](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247534298&idx=1&sn=21ad88daaedaf33566862e27efc29f5e&chksm=fbd7f4b6cca07da043296b689ededb9923057f68e551c2af0f73a805bf4b38f6c9279b019d84&scene=27#wechat_redirect) | 粗排 | 2021-03-08 |
| 阿里飞猪 | [阿里飞猪主题与交互式推荐技术实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247533960&idx=2&sn=6c73cfb81818554c26add442a3fc92af&chksm=fbd7f7e4cca07ef24457e2a9894e99204c895785202d72257d531b773760b8d1e21df9f08858&scene=27#wechat_redirect) | 推荐 | 2021-03-04 |
| 京东 | [京东搜索在线学习探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247533885&idx=1&sn=4bacb967f194d00e69798f9a3b0eeed2&chksm=fbd7f751cca07e47e466094605201bfcc5feff89e273a1aa59b64d5aeb6ffb0b2aaee9a99678&scene=27#wechat_redirect) | 搜索 | 2021-03-01 |
| 爱奇艺 | [爱奇艺短视频推荐：粗排篇](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247533568&idx=1&sn=2b8c694ff43bb451ff1e70b49a7bd97b&chksm=fbd7f66ccca07f7a29d0eb0389cd4231707d6588219af0fff94b22e43d8106161172aff9f16c&scene=27#wechat_redirect) | 粗排 | 2021-02-27 |
| 快手 | [多目标排序在快手短视频推荐中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247533308&idx=1&sn=f25852e94c1f0c3535312961342b2933&chksm=fbd7f090cca07986161d65abbf1f8bdc7858775a75de302f591c31ed992e9816682d44e6b311&scene=27#wechat_redirect) | 多目标&多任务 | 2021-02-24 |
| 阿里 | [阿里粗排技术体系与最新进展](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247530926&idx=1&sn=43527db30cd5d0584a8f112426d8720f&chksm=fbd7cbc2cca042d4c0620396c3acc6752c8b6a9f5c7980a9f7ac44a72c040e0d0763ced31606&scene=27#wechat_redirect) | 粗排 | 2021-02-21 |
| 阿里淘系 | [EdgeRec：边缘计算在推荐系统中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247529736&idx=1&sn=d24b824c6ff0841a851f123800b87ea4&chksm=fbd7c764cca04e722b39cc29e05eb4e5009ea9f66a5b0e502653c8086a56defb1dec257893aa&scene=27#wechat_redirect) | 推荐 | 2021-02-17 |
| 阿里淘系 | [阿里深度树匹配召回体系演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247529654&idx=1&sn=77b68c348d19685b57523056b8762c8c&chksm=fbd7c6dacca04fcc3edf402e37fef4bc7eacfad21a99c37e28131501fbbe3a74033ded30732b&scene=27#wechat_redirect) | 召回 | 2021-02-15 |
| 58同城 | [多目标推荐场景下的深度学习实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247529612&idx=1&sn=57e147d705ba3faebb8acb91e18c5bc6&chksm=fbd7c6e0cca04ff616575d710a545f98e79db90394e76b9d5f5f3589124efa8a88d6f99aaed1&scene=27#wechat_redirect) | 多目标&多任务 | 2021-02-13 |
| 阿里淘系 | [5大经典排序算法在淘宝“有好货”场景的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247529074&idx=1&sn=877e42d49b4474eb488a32ec3b5e9108&chksm=fbd7c01ecca04908f40d3907a719b850cbf1cfb87afb83e4cc62e8255b7714bd65504d639e54&scene=27#wechat_redirect) | 推荐 | 2021-02-11 |
| 58同城 | [深度学习在搜索排序业务中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247528876&idx=2&sn=717b0426ccbcc168d0fa9fbad3fc2c8a&chksm=fbd7c3c0cca04ad662db295c96894f85b89a36d074565a326a53ad9d8870944bce48da2be748&scene=27#wechat_redirect) | 搜索 | 2021-02-10 |
| 蘑菇街 | [基于ESMM模型的MTL多目标优化实践——用户活跃度影响排序机制——蘑菇街首页信息流推荐](https://zhuanlan.zhihu.com/p/344165004) | 多目标&多任务 | 2021-02-08 |
| 阿里淘系 | [MMoE算法在家居内容推荐中的应用与实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650418474&idx=1&sn=6b1e3ff914e68607c006a07a5b880296&chksm=8396e532b4e16c24734511e21872e995f5191943628eca791eb819a3899cfd6904996d09f461&scene=27#wechat_redirect) | 多目标&多任务 | 2021-02-05 |
| 阿里飞猪 | [阿里飞猪搜索技术的应用与创新](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247523713&idx=1&sn=06a41fb141e2fcdd0b723874f5090481&chksm=fbd72fedcca0a6fbb4f4b89720e379bde71a9f25579e2886b7629ad3e7f4f7eb7b550ca9e9f5&scene=27#wechat_redirect) | 搜索 | 2021-02-03 |
| Hulu | [Hulu在Content Embedding的探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247522939&idx=1&sn=8dfedad371667ef3ebd5621cbb882a25&chksm=fbd72817cca0a1015e484b805bd5ef5c9442b47e1f45a9643cfc56bbc7a5787bad19ae4d1351&scene=27#wechat_redirect) | 召回 | 2021-01-29 |
| 阿里妈妈 | [想为特征交互走一条新的路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247522902&idx=1&sn=55111acdfdc00dc59fc0fb10dfe9e0dc&chksm=fbd7283acca0a12c23a5b77a2413c25956a63c348c48f9fe01787d3d155d5fbcd183a0f09e90&scene=27#wechat_redirect) | 精排&CXR预估 | 2021-01-27 |
| Facebook | [Facebook’s News Feed ranking algorithm](https://zhuanlan.zhihu.com/p/348595873) | 推荐 | 2021-01-26 |
| 知乎 | [知乎搜索排序模型的演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247522599&idx=1&sn=24ab674235a3bc1a3b9944894bb6715f&chksm=fbd72b4bcca0a25d7287bf4ad0ec5becdb1ceb800966c9f7cf1ecacf807187f3a5a9d13f71a0&scene=27#wechat_redirect) | 搜索 | 2021-01-25 |
| 知乎 | [知乎搜索文本相关性与知识蒸馏](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247520759&idx=1&sn=4aaab934ad388ce03d3af0a3e812ce9e&chksm=fbd7239bcca0aa8d37d22880608f7704c51104f79b5bee016a7b4692dc3340e983dae0c0fa31&scene=27#wechat_redirect) | 搜索相关性 | 2021-01-15 |
| 蘑菇街 | [基于ESMM模型的多目标优化实践——蘑菇街商城篇](https://zhuanlan.zhihu.com/p/338515054) | 多目标&多任务 | 2021-01-08 |
| 贝壳 | [贝壳用户偏好挖掘的思考与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247519854&idx=2&sn=b373b930f2409b56c3d27193f8b7fd1f&chksm=fbd73c02cca0b514bf784919121c46963cdca4aa944336dfeb8c5b7f5b5211de0b746f4eee23&scene=27#wechat_redirect) | 偏好挖掘 | 2021-01-07 |
| 阿里妈妈 | [算力经济时代：阿里展示广告引擎的"柔性"变形之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247519343&idx=1&sn=4f23cfbc240fcaac5d05a6411362a3fa&chksm=fbd73e03cca0b715ff529d524b1d36efc4a7c52c904fdc07f5858ce06943de1e4acd381b0ae5&scene=27#wechat_redirect) | 广告 | 2021-01-04 |
| 腾讯 | [Angel图神经网络算法在推荐场景下的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247518591&idx=2&sn=483cec95afbfc61aa0b6736ebae47b3c&chksm=fbd73b13cca0b205887dfa2e03a092cb9bda9b2f22e823ea378ef96cf24a9a75775c47f9f170&scene=27#wechat_redirect) | 推荐&图网络 | 2020-12-31 |
| soul | [灵魂匹配：陌生社交Soul的增长机制](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247518142&idx=1&sn=6c7484ca8f4d55fc96e2e8a87ab4cbb5&chksm=fbd735d2cca0bcc4d56252639dd615aee574a520cc37ce7d6401cc7ef44f7e8f9b79739e78f9&scene=27#wechat_redirect) | 用增 | 2020-12-26 |
| 腾讯 | [Angel推荐算法在游戏推荐中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247517980&idx=2&sn=bc82b69449a005f76284a475c46a7ec2&chksm=fbd73570cca0bc66302d7bdb893e4c391197004baf376a0fa3e52ad68052ba7bc66ee0e0a723&scene=27#wechat_redirect) | 推荐 | 2020-12-24 |
| 阿里淘系 | [序列检索系统在淘宝首页推荐重排中的实践（附重排经典论文合集）](http://mp.weixin.qq.com/s?__biz=MjM5MzY4NzE3MA==&mid=2247489906&idx=2&sn=ef3edb0c5ea102b92beaf3731f928af3&chksm=a6926a9f91e5e389230aa102870b24102d73e7073c75c5bfd997f8d8b8d6b9b14808326ff011&scene=27#wechat_redirect) | 重排 | 2020-12-18 |
| 蘑菇街 | [蘑菇街增量学习番外篇三：deepFM的动态正则实践](https://zhuanlan.zhihu.com/p/337649676) | 推荐 | 2020-12-18 |
| 阿里淘系 | [序列检索系统在淘宝首页信息流重排中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247517708&idx=1&sn=d44835c9bc1099aeb6b6c40b8c32fad5&chksm=fbd73460cca0bd769dfa2a3379649c14b78528cfb8e9df0fa3807bbcf6cef3f9324a52a83a97&scene=27#wechat_redirect) | 重排 | 2020-12-17 |
| 蘑菇街 | [蘑菇街增量学习番外篇一：动态正则之tensorflow中div转mod设计（含代码实现）](https://zhuanlan.zhihu.com/p/270354109) | 推荐 | 2020-12-17 |
| 蘑菇街 | [蘑菇街增量学习番外篇二：优化器设计理论篇（AdamW、AdaDeltaW、FTRL）](https://zhuanlan.zhihu.com/p/329877052) | 推荐 | 2020-12-17 |
| 丁香园 | [再谈搜索中的Query扩展技术](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247517070&idx=2&sn=367376c143ca8f5e526b33d93518ea16&chksm=fbd731e2cca0b8f4c97ea4f22464c6ee101e853f2a95b8159763c72e723d8902843a13970bf9&scene=27#wechat_redirect) | 搜索 | 2020-12-14 |
| 贝壳 | [贝壳商业化算法中台架构实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247516794&idx=1&sn=a3f2243dfba429f3956514c2e00aca1b&chksm=fbd73016cca0b900bce56933e86d12237c7ca5e7ada3532d104e18e5a03d60167683b23aaa38&scene=27#wechat_redirect) | 工程相关 | 2020-12-10 |
| 美团 | [ICDM论文：探索跨会话信息感知的推荐模型](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651755958&idx=2&sn=bb2a7e9e3817d9993a9137dfeb6b5ec4&chksm=bd124cfb8a65c5ed3453a6473b556df1968e9f983da94bcab6610f718bfed2b37be5bd3ad7ae&mpshare=1&scene=1&srcid=0117wmg82Cvm9SxD2roqqbzV&sharer_sharetime=1673957290926&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2020-12-10 |
| 腾讯微信 | [浅谈微信AI在通用图像搜索领域的探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247516481&idx=2&sn=fe9b5f5d0caaa8c142abdb1803336c8f&chksm=fbd7332dcca0ba3b3d27055d9325be56b0fc54106cd0d36ad3a3ac88ce1c3d0e49ff1ebb5c33&scene=27#wechat_redirect) | 搜索 | 2020-12-09 |
| 腾讯微信 | [微信AI从识物到通用图像搜索的探索揭秘](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649754988&idx=1&sn=e1d382f8337b5b29085f7e495e85cd0d&chksm=becc9e1789bb1701c6dffa631ae135217240fb436bbc542b36af7a8b6a64b2c7c6f3bb988ce8&scene=27#wechat_redirect) | 搜索 | 2020-12-04 |
| 阿里 | [信息流推荐的用户增长机制](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247513875&idx=1&sn=75f718e9c7a27e37a753bd7d7e3c1fd1&chksm=fbd7057fcca08c690d7b5aab77ff92a374e8f88b722815c421e0d69d1fecad73fec888969a7c&scene=27#wechat_redirect) | 用增 | 2020-12-02 |
| 腾讯 | [主流Embedding技术解析](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247513629&idx=2&sn=afba7c17c3f59a9ad04598584aaf181a&chksm=fbd70471cca08d67fd0a4feb6febf613746e1bce6b03e72f6a47c82886f9008e4d1a0dec2683&scene=27#wechat_redirect) | 召回 | 2020-12-01 |
| NVIDIA | [Merlin：基于深度学习的推荐系统框架](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247513593&idx=2&sn=376de870c28403fa35087e438a4e6279&chksm=fbd70795cca08e838ee482038a321031db6f4725accb631d92587f111a856ea7217a7727b083&scene=27#wechat_redirect) | 推荐 | 2020-11-29 |
| 美团 | [美团本地生活场景的短视频分析](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247512282&idx=2&sn=7174703572f4609d8cc471de41f84762&chksm=fbd702b6cca08ba085c7c2e84b47c4cea10be3400790a6ada49bf1e19e6dd2f996b89685a534&scene=27#wechat_redirect) | 其他 | 2020-11-22 |
| 网易 | [网易云音乐推荐中的用户行为序列深度建模](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247512229&idx=1&sn=fe8430b49e6d5fd73e0f9c5cd9d0aaf6&chksm=fbd702c9cca08bdf665cb5628d380e25073dd18366372ff75243f0d9491760f6030a10aebc01&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-11-20 |
| 阿里文娱 | [阿里文娱深度语义搜索相关性探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247512107&idx=2&sn=ce7ce209d594b0574518e5b62a60998a&chksm=fbd70247cca08b5190e1b06ed87f036fc71c17bdda40fb80cbe69420ac7fe22f4eda2c554398&scene=27#wechat_redirect) | 搜索相关性 | 2020-11-16 |
| 腾讯微信 | [搜索query意图识别的演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247512053&idx=2&sn=0ab4ade5ee6c83f1f53a0e03583dc822&chksm=fbd71d99cca0948f7fb6e29943d559214fb55373287ee66cd7c786986f673b9d587ef1d6a3f2&scene=27#wechat_redirect) | 搜索 | 2020-11-15 |
| 蘑菇街 | [蘑菇街首页推荐多目标优化之reweight实践：一把双刃剑？](https://zhuanlan.zhihu.com/p/271858727) | 多目标&多任务 | 2020-11-13 |
| 腾讯微信 | [要提升微信看一看推荐混排的长期收益？试试深度强化学习](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247511450&idx=2&sn=57ce9b8d1493fa72f4255dc9b0b866f2&chksm=fbd71ff6cca096e0f798537bcb9e75b88dd777013b7a9fc94b42fa5e7f7368347fb2c566643d&scene=27#wechat_redirect) | 推荐 | 2020-11-12 |
| 爱奇艺 | [TensorFlow Ranking框架在爱奇艺海外推荐的实践与应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247511245&idx=2&sn=06e8909f8955594394daef5c43f1b538&chksm=fbd71ea1cca097b7373fa24f9d398b58747ef06c408bd798c1995a37a11132e66809306a2ba0&scene=27#wechat_redirect) | 工程相关 | 2020-11-09 |
| 腾讯 | [ZeroSearch：腾讯新一代搜索引擎](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247511217&idx=2&sn=021d8fba7ab6decca283d95e5da00600&chksm=fbd71eddcca097cb5da1b73eee9cac0b07277be93fd08cadda170726459fa2a385d376c733bd&scene=27#wechat_redirect) | 工程相关 | 2020-11-08 |
| 蘑菇街 | [文本相关性在蘑菇街搜索推荐排序系统中的应用](https://zhuanlan.zhihu.com/p/265522400) | 搜索相关性 | 2020-10-30 |
| 360 | [360展示广告智能化演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509951&idx=1&sn=04462583ebe942a12dc8260f7d909ae2&chksm=fbd715d3cca09cc52f5a2aff66e08ad655eb4dd6b7e035d9134a4afceca2c76d19feacf501ce&scene=27#wechat_redirect) | 广告 | 2020-10-30 |
| 网易 | ["全能选手"召回表征算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509607&idx=1&sn=341212c60824f8c636ee7e8b64a63d62&chksm=fbd7140bcca09d1d52dfb1c10c180feffe3641d2611b46497f08f9722a66cbd6b08436013be4&scene=27#wechat_redirect) | 召回 | 2020-10-28 |
| 腾讯 | [腾讯增长技术：智能投放篇](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509524&idx=1&sn=a65fb689f9b013fe06c44f1e4b2e1b84&chksm=fbd71478cca09d6eadfa3c06c921a47681339c0fa42bd960d66057f07e436e31ed08e92dfeda&scene=27#wechat_redirect) | 广告 | 2020-10-26 |
| 阿里淘系 | [阿里深度召回模型实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509261&idx=1&sn=17a4b327f46ea40bdf4f7481f8739311&chksm=fbd71761cca09e778f3e05860d2e1333c0ba9e32c6854f1040991478f5965262ef1a0f849b4c&scene=27#wechat_redirect) | 召回 | 2020-10-23 |
| 爱奇艺 | [爱奇艺视频精彩度分析算法及应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509245&idx=2&sn=e32f855fa4bcabdd98aef05acc540c17&chksm=fbd71691cca09f878448bf905db8e11119d4ad2482ab48132145ef3ba51fd868448499d73047&scene=27#wechat_redirect) | 其他 | 2020-10-22 |
| 阿里淘系 | [阿里新突破！动态网络表征学习在推荐领域的创新与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509060&idx=1&sn=be61e643a3de80d8b0bd028cdb5b6827&chksm=fbd71628cca09f3e637db58ce5fc43254fa18ad16779cd6eaf6f1c2d70bbf9e787b420d4116e&scene=27#wechat_redirect) | 推荐&图网络 | 2020-10-17 |
| 腾讯 | [Angel：深度学习在腾讯广告推荐系统中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247509016&idx=1&sn=aa4c859d268ca02ff869d0930f154463&chksm=fbd71674cca09f62c62bcc8fa9704df9d041c2c5271bdf4eb4bb9cf7e12bb407469e07868017&scene=27#wechat_redirect) | 推荐 | 2020-10-14 |
| 丁香园 | [医疗搜索中的query词权重算法探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247508936&idx=2&sn=78be7e9852a78ddf0da07198b6c7978b&chksm=fbd711a4cca098b245bcdba6932d42927a95ebf01fb949f3e4dbf8d74efc63e6c619357fc702&scene=27#wechat_redirect) | 搜索 | 2020-10-13 |
| 阿里淘系 | [推荐算法三视角:矩阵，图，时间线](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650411171&idx=1&sn=b05ff627563bb01d6d29e9482e7e5cc3&chksm=8396d8bbb4e151ad9353e25ab55df7dcb42181c74841db869b9b742994f97109cf423b998685&scene=27#wechat_redirect) | 推荐 | 2020-10-13 |
| 阿里淘系 | [阿里强化学习重排实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247508674&idx=1&sn=098ce77e2947f6e7bb28e56f320d7633&chksm=fbd710aecca099b8e4facf74dc0de9c6023d022c701d012e181c6286295c7578601b5cf78979&scene=27#wechat_redirect) | 重排 | 2020-10-04 |
| 网易 | [Embedding在网易严选搜索推荐中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247508638&idx=1&sn=97aa5c7ee4a7981942f40eed91853645&chksm=fbd710f2cca099e45307f0622d243ba543164c14131bbc8cb5a410b4a8ea974f9e1562b34cde&scene=27#wechat_redirect) | 召回 | 2020-10-01 |
| 阿里淘系 | [内容推荐算法：异构行为序列建模探索](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650411013&idx=1&sn=de621be8767a9e4e9c8de312ecfd5702&chksm=8396d81db4e1510b4a88441595810d48d6ab6c4a4d295fd7b543152603820e93deeba9b52c22&scene=27#wechat_redirect) | 推荐 | 2020-09-27 |
| 美图 | [美图个性化推送的 AI 探索之路](https://zhuanlan.zhihu.com/p/259668668) | 推荐 | 2020-09-26 |
| 蘑菇街 | [蘑菇街推荐算法之迷——self attention不如traditional attention？](https://zhuanlan.zhihu.com/p/256252184) | 推荐 | 2020-09-24 |
| 阿里淘系 | [向量召回在躺平APP的实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650410892&idx=1&sn=69a89072e83f6ff2b9333622ad390fdd&chksm=8396c794b4e14e829b625fa26568dd112f94edbdc97ec4984a2daf5ee5187e2283c397e36d48&scene=27#wechat_redirect) | 召回 | 2020-09-22 |
| 百度 | [同义变换在百度搜索广告中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247508089&idx=1&sn=456558fbe9754cb3b55c6af563504ed1&chksm=fbd71215cca09b03d3ea2fcc44fe511a44823ced8947375a3af9f925c41fbaafd9a38bddaba2&scene=27#wechat_redirect) | 广告 | 2020-09-21 |
| 阿里 | [阿里跨域点击率预估混合兴趣模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247507741&idx=2&sn=7d147d3db65d445cd6e17fd943643ebf&chksm=fbd76d71cca0e467a1d6add9d396f1722534d13c9a6c7bacb644c92105f5830bb04a240360ee&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-09-18 |
| 腾讯 | [腾讯信息流热点挖掘技术实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247507652&idx=1&sn=9d3333523ef629aa4286c0bdc669ca22&chksm=fbd76ca8cca0e5be2c9bd7e5e59c5919a7a601eeb5d25ec913877f2827262fe96e0c9d56e6ce&scene=27#wechat_redirect) | 热点挖掘 | 2020-09-16 |
| 阿里淘系 | [阿里新一代Rank技术](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247507509&idx=1&sn=5f0db1f772d6d8c39016c54318bbc1b1&chksm=fbd76c59cca0e54f82bc64bd1480e1bf36eb1d3323eaf0ce48c9362cdf2665aaafde8c1943a2&scene=27#wechat_redirect) | 推荐 | 2020-09-14 |
| 360 | [TensorNet——基于TensorFlow的大规模稀疏特征模型分布式训练框架](http://mp.weixin.qq.com/s?__biz=MzkzNzI0MDMxNQ==&mid=2247487550&idx=1&sn=68af975e460637783d0a860bfb2d694d&chksm=c29323aaf5e4aabc45b4f705d6c69583960fdae2638f2b3a5252f507ecfa088c92e1f72c6ad8&mpshare=1&scene=1&srcid=0117tJyokgtmE6m24zBKj7kA&sharer_sharetime=1673957367314&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 工程相关 | 2020-09-14 |
| Airbnb | [搜索推荐广告排序艺术-Airbnb搜索结果多样性优化](https://zhuanlan.zhihu.com/p/239824669) | 搜索 | 2020-09-13 |
| Airbnb | [搜索推荐广告排序艺术-Airbnb搜索深度学习排序算法进化](https://zhuanlan.zhihu.com/p/238095817) | 搜索 | 2020-09-12 |
| 腾讯看点 | [腾讯看点投放系统介绍：推荐系统的进化伙伴](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649749269&idx=2&sn=deabfe04574815220abad87d9dc9d415&chksm=bed3646e89a4ed782643c014b20e5fb4b2fa114ba8280e168c9f9fbeeef85f6cf758c56fef4e&scene=27#wechat_redirect) | 推荐 | 2020-09-07 |
| 蘑菇街 | [蘑菇街首页推荐视频流——增量学习与wide&deepFM实践（工程+算法）](https://zhuanlan.zhihu.com/p/212647751) | 推荐 | 2020-09-04 |
| 阿里妈妈 | [阿里妈妈深度树匹配技术演进：TDM->JTM->BSAT](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247507022&idx=1&sn=aa4a99562a274b5fd07e5f987a5dc807&chksm=fbd76e22cca0e734f4bc319ec3b908b9b3f200bda80e20b8f65836aac4445bc6a14675aa174e&scene=27#wechat_redirect) | 召回 | 2020-09-04 |
| 58同城 | [深度学习在商业排序的应用实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247506940&idx=2&sn=df6d88efa9f45dc7e2e4592018979692&chksm=fbd76990cca0e08637035afb74fb94cfaec3250c81c8744f41ac6be316d2bee96db16c9fc56c&scene=27#wechat_redirect) | 推荐 | 2020-09-03 |
| 京东 | [CSCNN：新一代京东电商广告排序模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247506872&idx=1&sn=26b673e5594ec07b3e56b94983d04741&chksm=fbd769d4cca0e0c24f0f96ce2f1eb995065dfbdb17f99cb8bcaa15cbb878673040854a0c0b1b&scene=27#wechat_redirect) | 广告 | 2020-09-02 |
| 腾讯微信 | [微信「看一看」 朋友在看的增强推荐系统](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649749174&idx=1&sn=ba2bc3de97799879b186feb66e60ec1c&chksm=bed365cd89a4ecdbefb2cf3b631090947788c02fa42323cd19a943aeaa6363ce4bca85e93a4d&scene=27#wechat_redirect) | 推荐 | 2020-08-31 |
| 阿里淘系 | [淘宝搜索模型核心技术：用户建模篇](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247506444&idx=1&sn=48bc7d6d70b336237137a3191894d711&chksm=fbd76860cca0e176d6ba80ef7b7815634578b8468d7e9177158f2426b6d1a27f7b701fbfa940&scene=27#wechat_redirect) | 搜索 | 2020-08-29 |
| 腾讯 | [10 分钟快速入门海量数据搜索分析引擎 Elasticearch](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649749100&idx=2&sn=7b35927876b101deee529bdb2649b8fb&chksm=bed3651789a4ec017c9a7f563ab7e5aab406a5a75aa87a2b89851755605d9c0784ce1099d8cb&scene=27#wechat_redirect) | 工程相关 | 2020-08-28 |
| 阿里淘系 | [从阿里的User Interest Center看模型线上实时serving方法](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247506358&idx=2&sn=0736cc1bc0d11f4f1ce99979697c29d6&chksm=fbd76bdacca0e2cc405e0f7b689a17f3d752b9fbd5087b0f06b14e24fb2008b6dd43bdd8153f&scene=27#wechat_redirect) | 工程相关 | 2020-08-27 |
| 阿里飞猪 | [阿里飞猪个性化推荐：召回篇](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247506153&idx=1&sn=6ce4840ec9642deb8e1c97efdc727390&chksm=fbd76a85cca0e393c44815b55af12ceca91546d32b5aa6b6340cfb3bb4dbed94d88c5f741cb0&scene=27#wechat_redirect) | 召回 | 2020-08-23 |
| 微博 | [微博推荐算法实践与机器学习平台演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247505895&idx=1&sn=d449cd607a21e01805db245be8289de6&chksm=fbd7658bcca0ec9d27eb71a01e8b08711802f59cb0c04aa6059eb0d60b895212de8b8e0b5a38&scene=27#wechat_redirect) | 推荐 | 2020-08-20 |
| 阿里妈妈 | [阿里定向广告最新突破：面向下一代的粗排排序系统COLD](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247505774&idx=1&sn=63efc686d3dda67fa4631e5550560476&chksm=fbd76502cca0ec141440482e048196119101abd0a56dd5dba7c9a18f46ba8f0358e3a458408b&scene=27#wechat_redirect) | 粗排 | 2020-08-18 |
| 阿里妈妈 | [阿里妈妈：基于动态背包的多场景广告序列投放算法](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247505578&idx=1&sn=bc6f551bc83039cebe016ba87cdf8a46&chksm=fbd764c6cca0edd0befcbb887b5b15f10296de6cd6d92ed3382221fcb367c92079b99c895914&scene=27#wechat_redirect) | 广告 | 2020-08-15 |
| 阿里淘系 | [EdgeRec：边缘计算在淘宝推荐系统中的大规模应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247504918&idx=1&sn=d4cb633276121dc4f09329cf9d231539&chksm=fbd7667acca0ef6cc9d0f21d309b5b28b15f0452f43d33055a1b9562a9519ad36c032ab961f0&scene=27#wechat_redirect) | 工程相关 | 2020-08-05 |
| 58同城 | [多业务融合推荐策略实践与思考](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247504377&idx=1&sn=7ca002dd3bfd00a14c93a519b3765a04&chksm=fbd76395cca0ea83b55807543fde6e8fd7879af67d5a4079365493669752cdff06fac5d632c5&scene=27#wechat_redirect) | 多目标&多任务 | 2020-07-29 |
| 腾讯微信 | [微信"看一看"个性化推荐：排序篇](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247504009&idx=2&sn=c3d07faaf34416790456eac5be094049&chksm=fbd762e5cca0ebf33eb7f3de1f9c1539ef5bf9fd7c8196bb85a9012ac7472f9c197b80ef8d56&scene=27#wechat_redirect) | 推荐 | 2020-07-21 |
| 腾讯 | [推荐系统 Embedding 技术实践总结](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247503968&idx=1&sn=d8fac671af39a87c9a74fb1aff327e41&chksm=fbd7620ccca0eb1aab16ab0e7d06e9c8975749808ca8d1191b442458280ea227b8ce4d90d865&scene=27#wechat_redirect) | 召回 | 2020-07-20 |
| 腾讯微信 | [微信"看一看"多模型内容策略与召回](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247503484&idx=2&sn=e2a2cdd3a517ab09e903e69ccb1e9f94&chksm=fbd77c10cca0f50642dde47439ed919aa2e61b7ff57bc4cbaacc3acaac3c620a1ed6f92684ab&scene=27#wechat_redirect) | 召回 | 2020-07-17 |
| 腾讯微信 | [微信「看一看」 推荐排序技术揭秘](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649747457&idx=1&sn=abfbd9e1c0889dda8c8511b44bbd6416&chksm=bed3637a89a4ea6c9be8915449ad6922da619d8ff0366272787bc93f149d7f36ae9e3ac2cc68&scene=27#wechat_redirect) | 推荐 | 2020-07-10 |
| 58同城 | [跨域推荐技术在58部落内容社区的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247502918&idx=1&sn=b461d08b22a9fd8ca2e711bb501b7d7a&chksm=fbd77e2acca0f73ccb2e2dad23ce817a968a9d83fcb0f5c8edda7d6566e77c2ff8bdcd1145a7&scene=27#wechat_redirect) | 推荐 | 2020-07-09 |
| 美团 | [BERT在美团搜索核心排序的探索和实践](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651752296&idx=1&sn=6c20fd97bfd9cc7e5557e40e867f123b&chksm=bd125e258a65d7335e7b649796248908d5a19c7d64f6f8935ab162c11539397feac3d830c3aa&mpshare=1&scene=1&srcid=0117uG6dCdQzn6ZP43n4Sclw&sharer_sharetime=1673957001505&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2020-07-09 |
| 阿里文娱 | [优酷视频元素内容召回系统：多级多模态引擎探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247502849&idx=1&sn=a9d6b7f727f99e877cb2a4a601773725&chksm=fbd77e6dcca0f77bb63e12273c5befbe00c24fed18525ee0d040acdb95a84f3a8def26707277&scene=27#wechat_redirect) | 召回 | 2020-07-08 |
| 阿里智能信息 | [机器学习在高德搜索建议中的应用优化实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247502251&idx=1&sn=19eb9bd0a7ad487e12af897c38115783&chksm=fbd77bc7cca0f2d178792a9ab4e1468f9f2179a81dbdfb3f6c96b30bea5e25d6bd01b10faf9a&scene=27#wechat_redirect) | 推荐 | 2020-06-27 |
| 腾讯 | [推荐系统 embedding 技术实践总结](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649747190&idx=1&sn=e850fae5360b7f1f4ee472dec70d5039&chksm=bed37d8d89a4f49b15da1394dbeb2f2934a1a2bb27aaa4e765fa6730a5658d5df2d076936122&scene=27#wechat_redirect) | 召回 | 2020-06-24 |
| 腾讯 | [一文搞懂 SQL：基础知识和业务实践总结](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649747167&idx=1&sn=8020e285502d9f47c77dd0c257364580&chksm=bed37da489a4f4b2c7d7e4082f8c05d42ac3ebdf2a49027c60ab603e9d65871aecbb6bb786e2&scene=27#wechat_redirect) | 工程相关 | 2020-06-22 |
| 阿里文娱 | [一文详解面向多级多模态场景的召回引擎](http://mp.weixin.qq.com/s?__biz=MzU5Mjc0MTM4NA==&mid=2247486983&idx=2&sn=f4b78f5507d299e34d8c0bc3fb73332d&chksm=fe1a5b60c96dd2763899db6db7a24a274593b4916732b8ddda97a40d2e37b4a476ab42baa18e&mpshare=1&scene=1&srcid=0117uqLWjE0PrSJaXfwrGQHE&sharer_sharetime=1673957934144&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 召回 | 2020-06-17 |
| 58同城 | [深度召回在招聘推荐中的挑战和实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247501908&idx=1&sn=2478b53f5a28eb4002bbfc9bef62001e&chksm=fbd77a38cca0f32ed9b04e6a2b38c3ce08c47f126863b1dafedefa5aa4d662d25d5537c384e2&scene=27#wechat_redirect) | 召回 | 2020-06-17 |
| 微博 | [内容理解在新浪微博广告中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247501693&idx=1&sn=da35a37ce1bfc8b43a26572acb5792d3&chksm=fbd77511cca0fc07beabb02dc15cd0f2f7f5ee9f0840ba512a4b3a373f4a676cb7156692bf5f&scene=27#wechat_redirect) | 内容理解 | 2020-06-12 |
| 腾讯 | [仅需少量视频观看记录，就可以精准推断你的习惯](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649747086&idx=1&sn=5d08665635003d57eba7bf9c2717fa66&chksm=bed37df589a4f4e35cac85f37c13cc30675c3285fba639bd657fd2dd7edbf35169de9777bcc1&scene=27#wechat_redirect) | 用户挖掘 | 2020-06-10 |
| 58同城 | [Embedding技术在房产推荐中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247501599&idx=1&sn=10c0eaa021ef4d7b39a82819bf4b0f66&chksm=fbd77573cca0fc658535625c70a550c297d10d8efcf6ca5640851d76e4cb0b051a9f5f6da62e&scene=27#wechat_redirect) | 召回 | 2020-06-10 |
| 阿里文娱 | [视频搜索太难了！阿里文娱多模态搜索算法实践](http://mp.weixin.qq.com/s?__biz=MzU5Mjc0MTM4NA==&mid=2247486719&idx=1&sn=48936c1a140f25a374ea5eb12807e636&chksm=fe1a5998c96dd08e39875af88eded481ade7e8f555a01b4dd9df06ea7156cc2e29381bc3e2b5&mpshare=1&scene=1&srcid=0117uXZesx2FgCB5y1sCUTNd&sharer_sharetime=1673957837931&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 搜索 | 2020-06-08 |
| 京东 | [京东电商搜索中的语义检索与商品排序](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247501196&idx=1&sn=978b373e1278c709fc53036614a240ab&chksm=fbd777e0cca0fef630da6ed55518775e22afba1e74cd2e09701e055533146f29c71876ba77c4&scene=27#wechat_redirect) | 搜索 | 2020-06-03 |
| 阿里文娱 | [PPT+视频\| 优酷视频元素内容召回系统：多级多模态引擎探索](http://mp.weixin.qq.com/s?__biz=MzU5Mjc0MTM4NA==&mid=2247486551&idx=1&sn=940a80be200e7fe0c1682405974039fc&chksm=fe1a5930c96dd026c1fa979b3989b13e21cecf8d451fd1448b0c534ff8f320ac41d48d0eba3a&mpshare=1&scene=1&srcid=01176HIzgCam1OfiESJDEnZd&sharer_sharetime=1673957847876&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 召回 | 2020-05-28 |
| 爱奇艺 | [爱奇艺深度语义表示学习的探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247500273&idx=1&sn=c8cf8e7a0515e1aeb0022417a6aeda9f&chksm=fbd7739dcca0fa8b8e4fdef2e1d669118de87c1ce1f2f1444bfe314610423fa2a3cf0c8c214c&scene=27#wechat_redirect) | 召回 | 2020-05-23 |
| 丁香园 | [搜索中的Query扩展技术](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247500267&idx=2&sn=0a38ea1f7d4a96a632b129ffbabc2d2c&chksm=fbd77387cca0fa91abbd69ad1885c44d05ab578886102d36e9ea11d9c7c529ebc47dbfa36d61&scene=27#wechat_redirect) | 搜索 | 2020-05-21 |
| 滴滴 | [搜索相关性算法在 DiDi Food 中的探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499792&idx=1&sn=59b8acac6ea9abe508825146983a4910&chksm=fbd7727ccca0fb6a56c5d677b7b6737bef02c7715b67d368ee551677a4110e241a14e66cf012&scene=27#wechat_redirect) | 搜索相关性 | 2020-05-16 |
| 阿里妈妈 | [深度时空网络、记忆网络与特征表达学习在 CTR 预估中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499645&idx=1&sn=a4d1e29381ab912861c3827399e22312&chksm=fbd74d11cca0c407e9149d5d80fba8b6b60e91b66a0688611dcbf6be2b89c2d136da181e0243&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-05-11 |
| 滴滴 | [基于强化学习的 Contextual Bandits 算法在推荐场景中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499525&idx=1&sn=638746fcd82ed8ebadb947c5848d8363&chksm=fbd74d69cca0c47fe102231f40b946c7bb0ae968c44061592bf161eb722f6fa71ee6a40b8fdb&scene=27#wechat_redirect) | 推荐 | 2020-05-09 |
| 腾讯 | [搜索中的 Query 理解及应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499470&idx=1&sn=6a6e80673353fb485a854ed2cffc5dcb&chksm=fbd74ca2cca0c5b4fb0622140eb9fa3cd15c860d06b24a4c7fc37e8b3db614af8c4ad9cbe0d3&scene=27#wechat_redirect) | 搜索 | 2020-05-07 |
| 华为 | [华为高级研究员谢凌曦：下一代人工智能计算模型探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499412&idx=1&sn=4bde0cbcf1d35fac55bda4733b0be356&chksm=fbd74cf8cca0c5ee48fd9e6448dddb2d885df8dffc11b4f9bce8952b4773a98ee7987b68ba7b&scene=27#wechat_redirect) | 其他 | 2020-04-30 |
| 阿里文娱 | [因果推断在阿里文娱用户增长中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499255&idx=1&sn=a7a6427c6c2bd74c728ef2d53c736814&chksm=fbd74f9bcca0c68d203296277c23e42f5a218d522bac4e23bfcfcde591be98e334e9f5cb67c8&scene=27#wechat_redirect) | 因果推断 | 2020-04-23 |
| 阿里文娱 | [阿里文娱搜索算法实践与思考](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499175&idx=1&sn=1c398e92f0712e4e5f545759d0a85692&chksm=fbd74fcbcca0c6dd11a04b493827ffdda06c69f6013b95c74c54c14f596cab0f303751f9e14d&scene=27#wechat_redirect) | 搜索 | 2020-04-20 |
| 携程 | [Bandit算法在携程推荐系统中的应用与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499139&idx=1&sn=c187e0108e9bd55b69e48d0c8de1887d&chksm=fbd74fefcca0c6f9290da7221b0d4b02a1d6a84913cf4950052b2050cd73e52b906d489f824e&scene=27#wechat_redirect) | 推荐 | 2020-04-19 |
| 美团 | [Transformer 在美团搜索排序中的实践](https://mp.weixin.qq.com/s/Oixc46P9rQeiMDjI-0j0cw) | 搜索 | 2020-04-16 |
| 阿里妈妈 | [广告CTR预估中用户行为学习和记忆建模](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247499010&idx=1&sn=138e92d3c22202b7b86c40d8f1bddd07&chksm=fbd74f6ecca0c678b3925526a0c1e4460521263444996eabe0e3224c2e38a243331520ad6f28&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-04-13 |
| 阿里飞猪 | [阿里飞猪“猜你喜欢”推荐排序实践](https://mp.weixin.qq.com/s?__biz=MzI1MzY0MzE4Mg==&mid=2247486489&idx=2&sn=e03b23d476d9864cd417f81c02f6e62e&chksm=e9d01cd8dea795ceb3d95d80ddab98f689d18ded9c0adc2f8175c665666a1d252c8db1d40f3c&scene=27) | 推荐 | 2020-04-08 |
| 阿里妈妈 | [CTR预估在动态样式建模和特征表达学习方面的进展](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498872&idx=1&sn=c7eb8e9147cb106b4122174981dce0b9&chksm=fbd74e14cca0c7027a2db1641d0e4e7bc16846035359684b702d462abdda8926ee7626bf4505&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-04-08 |
| 腾讯微信 | [热点挖掘技术在微信看一看中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498811&idx=1&sn=b138758fe26502935492f0411b5cf66e&chksm=fbd74e57cca0c741e1a51c21aa66c6117df5afe400d1656ea58a153e9f0b5a5bcba0233a42df&scene=27#wechat_redirect) | 热点挖掘 | 2020-04-05 |
| 阿里文娱 | [让广告算法做你的增长黑客！阿里文娱工程师这么做](http://mp.weixin.qq.com/s?__biz=MzU5Mjc0MTM4NA==&mid=2247485289&idx=1&sn=6b7edf8bc492bedeb51bb4677bb7d890&chksm=fe1a520ec96ddb18448cdb6c94c13e8ea642c887dd107705a9e00bfa07027a1afcbe29aecdb1&mpshare=1&scene=1&srcid=0117KL0KphjR4Mu3kvl0fOWG&sharer_sharetime=1673957914555&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 广告 | 2020-04-03 |
| 腾讯微信 | [揭秘微信"看一看"是如何为你推荐的](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498766&idx=2&sn=6169f19552682cc582746f6cf852905b&chksm=fbd74e62cca0c7745fdf1c6443f87e18dd85ecc943c7338b2cc1e6c06cd8bb6bae54444b397b&scene=27#wechat_redirect) | 推荐 | 2020-03-31 |
| 360 | [智能推荐算法在花椒直播中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498637&idx=1&sn=a91d76109129fa42e5910c2e2b5f68ef&chksm=fbd749e1cca0c0f75c8a9dc06c16b8d9a53cdf57eb370c07424d88eefd1ddb66928dd1bf2f7f&scene=27#wechat_redirect) | 推荐 | 2020-03-26 |
| 腾讯 | [搜索中的深度匹配模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498613&idx=1&sn=77f53f7e1edd2dc579cc49b5db803ad4&chksm=fbd74919cca0c00fdae51accb916b42a29d98bf3eb745f42bd9f17d9c4352ef9129ad13a0e5d&scene=27#wechat_redirect) | 搜索 | 2020-03-24 |
| 360 | [深度学习在花椒直播中的应用—推荐系统冷启动算法](http://mp.weixin.qq.com/s?__biz=MzkzNzI0MDMxNQ==&mid=2247487492&idx=1&sn=ba82daf0353c5eac7f6d9279e333546c&chksm=c2932390f5e4aa861692198be94febdac6fb05fc9909e4adc392f28e15b4dea9cf984f7579c9&mpshare=1&scene=1&srcid=0117ZsWh7O6AM8nXAR8xUfd0&sharer_sharetime=1673957379385&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 冷启动 | 2020-03-24 |
| 阿里淘系 | [深度学习在阿里B2B电商推荐系统中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498610&idx=1&sn=803bff13e7f663a63358ffef96b4525e&chksm=fbd7491ecca0c008f45e48180991ff7f2ccb70b6640ea9d9534c9cb6c2ddc4346bc848c4a3f3&scene=27#wechat_redirect) | 推荐 | 2020-03-23 |
| 美图 | [美图个性化推送的 AI 探索之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498181&idx=1&sn=f3ee8fc793cc47d069913017f5aa7c74&chksm=fbd74ba9cca0c2bfef5fd5a07805b35cc90d15146899125e6bf21be2294a811e42d851cd2c06&scene=27#wechat_redirect) | 推荐 | 2020-03-18 |
| 凤凰 | [信息流推荐在凤凰新闻的业务实践 ](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498125&idx=1&sn=52efbe5876151b48a917640f5f56c589&chksm=fbd74be1cca0c2f7b2f378a1b15339ef8697544c2b43bb9b51c7c9eaa79b6aea119d943786a9&scene=27#wechat_redirect) | 推荐 | 2020-03-16 |
| 省钱快报 | [深度学习在省钱快报推荐排序中的应用与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498064&idx=1&sn=66db655be0bcc5e6ee0dc58f869ef6eb&chksm=fbd74b3ccca0c22aacea4a7aca9e803f4044f78ad056983484ebc5ab0c718773ebd4ee8204ea&scene=27#wechat_redirect) | 推荐 | 2020-03-12 |
| 阿里文娱 | [广告算法在阿里文娱用户增长中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247498041&idx=1&sn=5c8b880a2be4075ee48388b27ce1a6e0&chksm=fbd74b55cca0c24382f3f10e6f2a8423e228c390339dc086d5f1fec034350e0574302587834a&scene=27#wechat_redirect) | 广告 | 2020-03-11 |
| 汽车之家 | [汽车之家推荐系统排序算法迭代之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247497757&idx=1&sn=fe521ea5a746be9ba0aa208506d716b8&chksm=fbd74a71cca0c3676f2681bb7917a12e77562d2c5b3d1e5def4a3eac3fc40bd57e12ef2548e5&scene=27#wechat_redirect) | 推荐 | 2020-02-28 |
| 阿里 | [阿里B类电商用户增长实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247497685&idx=1&sn=4af16b3d4d79ce2850b29717f7de1121&chksm=fbd745b9cca0ccaf7ab41fa2760befc0f0831d74e77c8ff430c4d31016efc1b21d27ac0cea1e&scene=27#wechat_redirect) | 用户增长 | 2020-02-26 |
| 阿里文娱 | [视频 \| 广告算法在阿里文娱用户增长中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247497357&idx=2&sn=9991d229219e36be78c954b46da1f3e3&chksm=fbd744e1cca0cdf764c33163c35b524299a13d78e803abfcb5e4f88fbb72c26c7dfdf00547dd&scene=27#wechat_redirect) | 用户增长 | 2020-02-11 |
| 阿里 | [阿里B2B：融合Matching与Ranking的个性化CTR预估模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247497190&idx=1&sn=c210c40cd365312038c5248752f9e187&chksm=fbd7478acca0ce9c3848d2e699ee4193b9cf08473a3f700d04f8514fa247594cded254aee600&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-02-05 |
| 阿里文娱 | [视频 \| 阿里文娱搜索算法实践和思考](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247497109&idx=2&sn=41f16c9b2a9513596553fcd9ff4bb6e2&chksm=fbd747f9cca0ceefffe34a2973623745034e7e94ee48b920b14282da022c9a30682e5dcdc7f5&scene=27#wechat_redirect) | 搜索 | 2020-02-03 |
| 腾讯 | [推荐系统中的深度匹配模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496713&idx=1&sn=07bb184081bf8590db12e63ccda6bf22&chksm=fbd74665cca0cf73e625c403d61bb3f1f0fdfe680566927f1b1cda7cb54a7b9ce17418c9690b&scene=27#wechat_redirect) | 推荐 | 2020-01-13 |
| 腾讯 | [一种全新的点击率建模方案](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649745235&idx=1&sn=d6031b0d45d1db8c61398e2d3b231bed&chksm=bed3742889a4fd3e3032cab8b95656b441d013d7b988a06f77d72aeb98315f4012bfd9b92b47&scene=27#wechat_redirect) | 精排&CXR预估 | 2020-01-10 |
| 阿里淘系 | [让机器读懂视频：亿级淘宝视频背后的多模态AI算法揭秘](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650405126&idx=1&sn=91a9e73ed4f2cc34ca1dac64144ae4d3&chksm=8395311eb4e2b808c516c1b4c9aac24ffe5e6ced9641370e73e6b13fc69512d6bb452a4bb1ba&scene=27#wechat_redirect) | 召回 | 2020-01-09 |
| 阿里淘系 | [阿里淘外商业化广告工程架构实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496498&idx=1&sn=058af2101d4a1ceda1ec04b30daf4d69&chksm=fbd7415ecca0c8488706ee79480560df06943ede862fc76e0917f29b663b3f30b220c37fee78&scene=27#wechat_redirect) | 工程相关 | 2020-01-08 |
| 爱奇艺 | [个性化海报在爱奇艺视频推荐场景中的实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496497&idx=2&sn=46afd0c464186e75ffb90b2af25bc3d6&chksm=fbd7415dcca0c84b056ed3b2aaa71c4469307e3a02e2766ae8f97f16c0bfe78b40e293868eaf&scene=27#wechat_redirect) | 推荐 | 2020-01-07 |
| 微博 | [机器学习在微博 O 系列广告中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496432&idx=1&sn=209510d8695aed74c65b2693d300e97b&chksm=fbd7409ccca0c98af6db5aaf452dd81b070f440326bdda5e505069608ddc3b448560c045a2f3&scene=27#wechat_redirect) | 广告 | 2020-01-06 |
| 知乎 | [Query 理解和语义召回在知乎搜索中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496409&idx=1&sn=7b2f5984d71454e1a2812321f6018cf8&chksm=fbd740b5cca0c9a37723c8c05b4e1cf95fd8678bc54e9b4591c09a7af06f2acf79e28276a502&scene=27#wechat_redirect) | 召回 | 2020-01-02 |
| 腾讯 | [腾讯在信息流内容理解技术上的解决方案](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649745156&idx=1&sn=744c59bceef156f5b9f84a28e3073708&chksm=bed3747f89a4fd69840a9c52dc8909d86c8f45ff7f634df48fc478860e43c62e1751ef04668e&scene=27#wechat_redirect) | 内容理解 | 2019-12-31 |
| 贝壳 | [DeepFM在贝壳房源详情页推荐场景的实践](https://mp.weixin.qq.com/s/bPjk1Rq19KmlPcfkYvVJVw) | 推荐 | 2019-12-30 |
| 阿里淘系 | [MMoE算法在淘宝躺平推荐中的应用实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496280&idx=1&sn=870b45e0f9bfda51a093ceabb9b51df2&chksm=fbd74034cca0c922893be32402905954f87d98ffa55aa879b45d9974870f29e15e2a1f5a1429&scene=27#wechat_redirect) | 多目标&多任务 | 2019-12-27 |
| 360 | [ElasticSearch 介绍及使用方法](http://mp.weixin.qq.com/s?__biz=MzkzNzI0MDMxNQ==&mid=2247487444&idx=1&sn=21618afb5aacc0ea224afdbb1e4fa155&chksm=c2933c40f5e4b5569ab5b0dd73d9a5233eee75dab93b53d23b9541e9230193a2560ce90869a8&mpshare=1&scene=1&srcid=0117mZBwP4XZjMn1x1cMkohc&sharer_sharetime=1673957427902&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 工程相关 | 2019-12-27 |
| 贝壳 | [wide&deep 在贝壳推荐场景的实践](https://mp.weixin.qq.com/s/rp6H_HydTbKiSanijDZwBQ) | 推荐 | 2019-12-18 |
| 阿里妈妈 | [阿里妈妈点击率预估中的长期兴趣建模](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247496080&idx=1&sn=70f79a37a6000965fa96bccf893b9c40&chksm=fbd743fccca0caeadb59820801597c51353b0a4ba080d2caf66eccb6644102c2fe674ffcb378&scene=27#wechat_redirect) | 精排&CXR预估 | 2019-12-18 |
| 阿里文娱 | [优酷 DSP 广告投放系统架构实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247495736&idx=1&sn=080c985a2e373e04496bce5db3cb1069&chksm=fbd74254cca0cb42324938685381d67217f3cb14cb6da64576cac58238264605b5f7e64d34a6&scene=27#wechat_redirect) | 广告 | 2019-12-06 |
| 腾讯微信 | [浅谈微视推荐系统中的特征工程](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649744942&idx=1&sn=7efd84c1371d785d719de481e3e6d44a&chksm=bed3755589a4fc43a2caa01c6579f6d10e65959c529a3be90da6e3938a09886eb8bcbd607ef1&scene=27#wechat_redirect) | 推荐&特征工程 | 2019-12-06 |
| 美图 | [多任务学习在美图个性化推荐的近期实践](https://zhuanlan.zhihu.com/p/89401911) | 多目标&多任务 | 2019-12-06 |
| 阿里妈妈 | [阿里妈妈新一代算法 JTM：如何优化大规模推荐？](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247495660&idx=1&sn=21a5b7e811d104162609d5fef993be79&chksm=fbd75d80cca0d496995ab1135ceb4734b90553a8fd82f4c970ed48212f3d0abd98f58e4e0864&scene=27#wechat_redirect) | 召回 | 2019-12-04 |
| 百度 | [MOBIUS：百度凤巢新一代广告召回系统](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247495618&idx=1&sn=42b06177dec45f33c29ab25d73b639a9&chksm=fbd75daecca0d4b8a6ae5c4854c40cc05bd6c7b67ac6ab45f74c05d425aafae9d54699a09c19&scene=27#wechat_redirect) | 召回 | 2019-11-29 |
| 腾讯 | [新一代海量数据搜索引擎 TurboSearch 来了！](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649744896&idx=1&sn=ac4361272c2d027631bbca9673b6dc10&chksm=bed3757b89a4fc6da6c516fde28c79c936e7b8dc4647fccebad77c616231c15a48102f28dd7e&scene=27#wechat_redirect) | 工程相关 | 2019-11-28 |
| 腾讯微信 | [RALM: 实时 Look-alike 算法在微信看一看中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247495507&idx=1&sn=a1e0cf988d2e366be58faf1110e4d885&chksm=fbd75d3fcca0d429b33c5a49053dd99a03e603b3230e950d0109f3c9dbe7ede21e1fa2a86752&scene=27#wechat_redirect) | 推荐 | 2019-11-25 |
| 360 | [向量化召回在360信息流广告的实践](https://zhuanlan.zhihu.com/p/93060649) | 召回 | 2019-11-23 |
| 腾讯 | [Bing搜索核心技术BitFunnel原理](http://mp.weixin.qq.com/s?__biz=MjM5ODYwMjI2MA==&mid=2649744830&idx=1&sn=950d79ac145ba6682fcfe096e0398c95&chksm=bed376c589a4ffd348ae826b7a855e034184629b798de48192443e727199ddb7a7c6bd594545&scene=27#wechat_redirect) | 工程相关 | 2019-11-19 |
| 腾讯 | [推荐系统中模型训练及使用流程的标准化](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247495039&idx=1&sn=35905df6cd4ef33d2ce505d284d3c8ad&chksm=fbd75f13cca0d605c17bf7a8b3b899b7798a590008625fcffbf00d77c2451249bbdc086d6b18&scene=27#wechat_redirect) | 工程相关 | 2019-11-04 |
| 360 | [360展示广告召回系统的演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247494825&idx=2&sn=92f59195e8e4e6b33af6dfa63df6a2b3&chksm=fbd75ec5cca0d7d36752d787d7fc0191b0ecccdb56bda335fa553635f241c20af1f768983f7d&scene=27#wechat_redirect) | 召回 | 2019-10-24 |
| 爱奇艺 | [爱奇艺效果广告的个性化探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247494579&idx=1&sn=b5274f98c5cfae81d1af68944d3252df&chksm=fbd759dfcca0d0c9f8ab04bebee04b0d7fd6fdd3eae87d3ef475fb26e03b402999c31621d034&scene=27#wechat_redirect) | 广告 | 2019-10-17 |
| 美图 | [深度学习技术在美图个性化推荐的应用实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247494558&idx=1&sn=10a6332147d713230d0fa4dbf9cdc897&chksm=fbd759f2cca0d0e4f5d39887a86b1d6efae13ad0540dc191fdbc8bb29120d0081a90c97b35f6&scene=27#wechat_redirect) | 推荐 | 2019-10-16 |
| 阿里智能信息 | [UC 信息流推荐模型在多目标和模型优化方面的进展](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247494398&idx=1&sn=cd08a71c4a7ec9a2d81107603fc4c437&chksm=fbd75892cca0d184585075b3315fe0386d37c174995a5a4b27e02db4117a13897678dbcb52ed&scene=27#wechat_redirect) | 多目标&多任务 | 2019-10-14 |
| 阿里智能信息 | [UC 国际信息流推荐中的多语言内容理解](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247494295&idx=1&sn=1218bfa026994967939fa676ed7dd5f9&chksm=fbd758fbcca0d1ede59b225e98add36cae74e9fd3006d42a054c73aaa4a87c75ef46684b9733&scene=27#wechat_redirect) | 内容理解 | 2019-10-09 |
| 凤凰 | [OCPC 广告算法在凤凰新媒体的实践探索](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247494020&idx=1&sn=df65908cdaf57d02eee8280d86d66949&chksm=fbd75be8cca0d2fe2d69d89a70eced34ba467acbf26fefe1bf40edea36a07e76406612383fd5&scene=27#wechat_redirect) | 广告 | 2019-09-25 |
| 阿里智能信息 | [浅谈 UC 国际信息流推荐](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247493952&idx=1&sn=f32e43f0e834d12649a3a6272b85ede0&chksm=fbd75b2ccca0d23a224032d999dd52ca3fa53529abf78c2cf3d4f5e9d52ef3a691bcf76bbdd1&scene=27#wechat_redirect) | 推荐 | 2019-09-23 |
| 58同城 | [58同镇下沉市场中的推荐技术实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247493807&idx=1&sn=7d0b5d89e6fb604794049ac29ccf6ecd&chksm=fbd75ac3cca0d3d526d65b0b55f9f34f2b2ca6d086a4222440b817a4434c359e979331a75917&scene=27#wechat_redirect) | 推荐 | 2019-09-18 |
| 微博 | [微博广告策略工程架构体系演进](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247493747&idx=1&sn=3288e75a42a8e93bc7ce34b47b811b9b&chksm=fbd75a1fcca0d3092046e1c3b0d961ef99edc8323426fdd78eae3693119a726328db7f0dd246&scene=27#wechat_redirect) | 工程相关 | 2019-09-16 |
| 快看漫画 | [快看漫画个性化推荐探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247493714&idx=1&sn=146ca2efa604b71b20ae166fb0cd6b85&chksm=fbd75a3ecca0d3280f88577c843d7ebf7c4b66f00134f2802e3863e17fa811eb8e328ca030a2&scene=27#wechat_redirect) | 推荐 | 2019-09-12 |
| 滴滴 | [解读：滴滴“猜你去哪儿”功能的算法实现](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247493496&idx=1&sn=16a9495c9a0452ef60e38bb129105b02&chksm=fbd75514cca0dc020fa508aa34e01a3c17949e70cbccd5531122556f14c7351d15da93775f17&scene=27#wechat_redirect) | 推荐 | 2019-09-04 |
| 阿里淘系 | [推荐系统走向下一阶段最重要的三个问题](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247493262&idx=1&sn=c5c2b9827c5de1d1311673523c96e3e7&chksm=fbd754e2cca0ddf47163df7559a20bb85a45633ecdc57f168874819225dffb4db19449c00cdc&scene=27#wechat_redirect) | 推荐 | 2019-08-28 |
| 360 | [深度学习在花椒直播的应用——Tensorflow 原理篇](http://mp.weixin.qq.com/s?__biz=MzkzNzI0MDMxNQ==&mid=2247487361&idx=2&sn=36cb82dd07dafa41ddd7b983f2c44649&chksm=c2933c15f5e4b503af0ac18437085f8928b09261e379e4d5a0628a386f2cefd4cbccb110ab60&mpshare=1&scene=1&srcid=0117dqnVg0mxFOFbynlpzCf9&sharer_sharetime=1673957459189&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 工程相关 | 2019-08-28 |
| 阿里妈妈 | [阿里妈妈深度树检索技术（TDM）及应用框架的探索实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247492994&idx=1&sn=6a787521ad85f37339f880bba0cc5d63&chksm=fbd757eecca0def8ac32a1c60f49ec933096833b5b55860074fd5d305499adc85d9f833fa333&scene=27#wechat_redirect) | 召回 | 2019-08-16 |
| 京东 | [京东电商推荐系统实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247492901&idx=1&sn=e0241e72bb057ed300fef994721a2a3b&chksm=fbd75749cca0de5f029b880bbe53914dfd789452d35cde78097f00a75f789f2508e452bf1805&scene=27#wechat_redirect) | 推荐 | 2019-08-08 |
| 阿里淘系 | [极测未来\|淘宝"千人千面"内容下的智能评测技术与实践](http://mp.weixin.qq.com/s?__biz=MzAxNDEwNjk5OQ==&mid=2650403666&idx=1&sn=96be637d3fd89472d326f09596a48e2d&chksm=83953b4ab4e2b25c514fd36904d0bad493aab91bcd4f30c4b59762b6b1fbd0b2aaa0509a0d4b&scene=27#wechat_redirect) | 推荐 | 2019-08-06 |
| 360 | [360搜索的百亿级网页搜索引擎架构实现](http://mp.weixin.qq.com/s?__biz=MzkzNzI0MDMxNQ==&mid=2247487340&idx=1&sn=e96e5e1034462b3fed38c98aef1627ca&chksm=c2933cf8f5e4b5ee13fd52fbaeda37679d5766aea514099c720a4bb131340521583ba2fd2582&mpshare=1&scene=1&srcid=0117LVG4Py92aQ9dr3ohqsMG&sharer_sharetime=1673957323507&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 工程相关 | 2019-07-31 |
| Hulu | [Hulu 在视频内容理解上的应用和最佳实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247492462&idx=1&sn=4f770371f0493448fab48af8750adb66&chksm=fbd75102cca0d81418aca45fe714c80838b5de34555cd561aec4d87cda710e56b744f953bbbc&scene=27#wechat_redirect) | 内容理解 | 2019-07-26 |
| 360 | [深度学习在360搜索广告 NLP 任务中的应用](https://mp.weixin.qq.com/s?__biz=MzI1MzY0MzE4Mg==&mid=2247484855&idx=2&sn=f0032b7a1611be3d87615f3aecc334de&chksm=e9d01576dea79c60aed6633bd1ff386a376c2bdb50aeaa35834644068f76a2a7f23649500fe1&scene=27#wechat_redirect) | 搜索 | 2019-07-18 |
| 阿里 | [阿里零售通智能导购推荐技术实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247492047&idx=1&sn=7db1f1eaadfdac75c5a0ae0e3a7beea1&chksm=fbd753a3cca0dab5fe09c091fb36c0ae9ba9ae83af38593d333bbdf61d97ee137b1577611ec0&scene=27#wechat_redirect) | 推荐 | 2019-07-11 |
| 网易 | [网易新闻推荐：深度学习排序系统及模型](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247491955&idx=1&sn=8d6258dd5330a86608191088ec5444a2&chksm=fbd7531fcca0da0945008445177aaaf07b72b61e990fd847e36a8f516eed0f0c93123409dddd&scene=27#wechat_redirect) | 推荐 | 2019-07-08 |
| 居理新房 | [低频少样本长验证周期场景下的算法设计](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247491927&idx=1&sn=5454d891f68f7c2d49cb453cf4c40f2d&chksm=fbd7533bcca0da2dc093950f0b2b95c4d525a6caf60fec117228be52afd2a498bb74812c0e92&scene=27#wechat_redirect) | 推荐 | 2019-07-05 |
| Hulu | [基于行列式点过程的推荐多样性提升算法](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247491883&idx=1&sn=9a28cb03a2e34ec380cd5ff789b8f48d&chksm=fbd75347cca0da51e1257f4de6824e77546f3eeb1e78090cd11ec71841f31cc4cf8562ab3151&scene=27#wechat_redirect) | 推荐 | 2019-07-03 |
| 途家网 | [Embedding 技术在民宿推荐中的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247491647&idx=1&sn=787f20dad8e613c0f72142df6789d91d&chksm=fbd75253cca0db45abed1a13b555f358ce059b4e9477afaeb872cab12d4fc310f119d65f797a&scene=27#wechat_redirect) | 召回 | 2019-06-25 |
| Airbnb | [深度学习在 Airbnb 中的探索与应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247491541&idx=1&sn=cd70f902ac265bfb36e95deac352f797&chksm=fbd4adb9cca324afc840c189ddae4f25ae5c1ee1b8405bd3d0c78c0293d87d85a516e1cfa1c0&scene=27#wechat_redirect) | 搜索 | 2019-06-21 |
| 阿里 | [当你打开天猫的那一刻，推荐系统做了哪些工作？](https://mp.weixin.qq.com/s?src=11×tamp=1675783003&ver=4336&signature=JXo7DrRlU7Hx9WJP0r7ozT7S1eVkuUt-AiIg21XL7Nz3OkHBzLWECkq4hTwtGtYY0NUnl5gLihW3hGnfr8dqXJIydi1e5uty4VX58eYccDtQI-jUVPhyMU9VvBdkCWkV&new=1) | 推荐 | 2019-06-04 |
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| 阿里妈妈 | [阿里妈妈：电商预估模型的发展与挑战](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247490293&idx=1&sn=4dcd1cf5f945c03c98ed3401afb7983d&chksm=fbd4a899cca3218f328a661da553b470e018eeeef2ca3bf2696140ef045f1805f89b8c3a596a&scene=27#wechat_redirect) | 精排&CXR预估 | 2019-05-20 |
| 阿里飞猪 | [POI 识别在飞猪搜索的探索与实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247490057&idx=1&sn=d676c16816c16a27abe5ce69c15feafa&chksm=fbd4a865cca321735c0c0a700e6210f80fa10cfa16aed6e8068dd601853a6285aa7f4601f2ad&scene=27#wechat_redirect) | 搜索 | 2019-05-10 |
| 达观数据 | [达观数据个性化推荐系统实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247488752&idx=1&sn=aaaed48b319d572990c93dc1e60a7ba2&chksm=fbd4a69ccca32f8a636b600a77504ab7689f8e90279ace41ae669268dba533e5b8ece9e7b2d3&scene=27#wechat_redirect) | 推荐 | 2019-03-11 |
| Hulu | [Hulu：视频广告系统中的算法实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247488177&idx=1&sn=ce32c5e9eaf50c9d7f5f3f075d632fc3&chksm=fbd4a0ddcca329cbc93e4fded3b83d59c7ab30d64206a1cf80e63289f925635bcf7eba6651a5&scene=27#wechat_redirect) | 广告 | 2019-02-25 |
| 阿里妈妈 | [「回顾」阿里妈妈：定向广告新一代点击率预估主模型——深度兴趣演化网络](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247487620&idx=1&sn=b3162fec93608788430f7e52236d998e&chksm=fbd4a2e8cca32bfea69c4e418e38d0c8709d2fe3395f74f73aaf48815ec8a41fc0d130ae4a1e&scene=27#wechat_redirect) | 精排&CXR预估 | 2019-01-28 |
| 搜狗 | [「回顾」深度学习新技术在搜狗搜索广告中的深化应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247487590&idx=1&sn=792f7c3a1cb05bd3c89660c2ceff3fed&chksm=fbd4a20acca32b1c3a9eff018b9e3e96a31425cab16d4a7241e0258221320266007e9c3e70f0&scene=27#wechat_redirect) | 广告 | 2019-01-23 |
| 美团 | [大众点评搜索基于知识图谱的深度学习排序实践](https://tech.meituan.com/2019/01/17/dianping-search-deeplearning.html) | 搜索 | 2019-01-17 |
| 知乎 | [「回顾」知乎推荐页Ranking经验分享](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247487240&idx=1&sn=f38e4a5cd73a2d2f1d52ee5eda418528&chksm=fbd4bd64cca334720629ba997aca98642bc1e1b25c422623ddf07e30cb9a5f5068cf22af0048&scene=27#wechat_redirect) | 推荐 | 2018-12-28 |
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| Airbnb | [Airbnb: 深度学习在搜索排序业务中的探索与演进（二）](https://zhuanlan.zhihu.com/p/52287783) | 搜索 | 2018-12-13 |
| Airbnb | [Airbnb: 深度学习在搜索排序业务中的探索与演进（一）](https://zhuanlan.zhihu.com/p/52146789) | 搜索 | 2018-12-11 |
| 51信用卡 | [「回顾」51信用卡的个性化推荐体系](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247486677&idx=1&sn=8fba1b390945dea3d15574f1465575f0&chksm=fbd4beb9cca337afbfc433e2873efb13ae87ec226bdd7dd9e1bee159a82a0201a9186c0a8449&scene=27#wechat_redirect) | 推荐 | 2018-11-21 |
| 饿了么 | [「回顾」饿了么推荐算法演进及在线学习实践](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247486538&idx=1&sn=32498d028a74dce05ffa4a4eee66e4b5&chksm=fbd4be26cca33730d988a9bd19e5bcd8034fc3388ff468853bfcf5367a4dc446c1ffcff355f8&scene=27#wechat_redirect) | 推荐 | 2018-11-07 |
| 饿了么 | [回顾·外卖推荐算法中有哪些机制与手段？](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247486253&idx=1&sn=5730d5ab24b87a5985ffa5ff10d34c79&chksm=fbd4b941cca330577e3755aea84d9026aca36a55490e7f71c447d613fca0ba5be77c00067490&scene=27#wechat_redirect) | 推荐 | 2018-10-12 |
| 阿里淘系 | [7种经典推荐算法模型的应用](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247486057&idx=1&sn=567a04976f82b07645992790196d223f&chksm=fbd4b805cca33113171e35d00054238b7a260052313ed32aa8050a4a7c9460638c65cb7a8389&scene=27#wechat_redirect) | 推荐 | 2018-09-16 |
| 阿里智能信息 | [回顾·神马搜索技术演进之路](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247485830&idx=1&sn=621393b30e179660de9b35d57da60752&chksm=fbd4bbeacca332fcfe9733a126f07386ad66c3a0381b5e0c2daa81c70d88d0d19048fad645c1&scene=27#wechat_redirect) | 搜索 | 2018-08-17 |
| 搜狗 | [回顾·搜狗信息流推荐算法交流](http://mp.weixin.qq.com/s?__biz=MzU1NTMyOTI4Mw==&mid=2247485411&idx=1&sn=3ac29da8b7a81869bd33679531e2cfe3&chksm=fbd4b58fcca33c998652a1e1a84b4dee7b825df919e1c68702938ee24728121617ac30f85878&scene=27#wechat_redirect) | 推荐 | 2018-07-02 |
| 美团 | [深度学习在美团点评推荐平台排序中的运用](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651746611&idx=1&sn=c9bf49b74c52ba3a091051772828fb54&chksm=bd12a87e8a6521689690ea992fe69ab4b37cbb3f77942e2900314033fdda361d9993af6698fa&mpshare=1&scene=1&srcid=0117WfBjqkaqVXB9LUCBJpti&sharer_sharetime=1673957092409&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 推荐 | 2017-07-28 |
| 美团 | [美团点评旅游搜索召回策略的演进](http://mp.weixin.qq.com/s?__biz=MjM5NjQ5MTI5OA==&mid=2651746412&idx=1&sn=885e98dd829dabbe3858d6b2ea9f954f&chksm=bd12a9218a652037b31b32188ff61258bdae61b3ab8bc5d326ac6f9d199cb1d83260701ff3ec&mpshare=1&scene=1&srcid=0117bKvljgSQqp4W9Kz9mPdU&sharer_sharetime=1673957061139&sharer_shareid=c032e8bde4d276951619cca1ff0debb1#rd) | 召回 | 2017-06-16 |