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awesome-knowledge-graph
整理知识图谱相关学习资料
https://github.com/husthuke/awesome-knowledge-graph
Last synced: 5 days ago
JSON representation
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理论及论文
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知识应用
- Towards Scalable Multi-Domain Conversational Agents: The Schema-Guided Dialogue Dataset
- Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
- Augmenting End-to-End Dialogue Systems with Commonsense Knowledge(2018)
- Towards Scalable Multi-Domain Conversational Agents: The Schema-Guided Dialogue Dataset
- Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering
- Augmenting End-to-End Dialogue Systems with Commonsense Knowledge(2018)
- Commonsense Knowledge Aware Conversation Generation with Graph Attention (IJCAI 2018)
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综述综合
- K-ADAPTER- Infusing Knowledge into Pre-Trained Models with Adapters
- A Frame-based Sentence Representation for Machine Reading Comprehension (ACL 2020)
- A Survey on Knowledge Graphs: Representation, Acquisition and Applications (2020)
- K-BERT: Enabling Language Representation with Knowledge Graph
- Inducing Relational Knowledge from BERT
- Knowledge Enhanced Contextual Word Representations (EMNLP 2019)
- A Survey on Knowledge Graphs: Representation, Acquisition and Applications (2020)
- A Frame-based Sentence Representation for Machine Reading Comprehension (ACL 2020)
- COMET: Commonsense Transformers for Automatic Knowledge Graph Construction (ACL 2019)
- ERNIE: Enhanced Representation through Knowledge Integration(2019)
- Knowledge Graphs (2020)
- Language Models as Knowledge Bases?
- KILT: a Benchmark for Knowledge Intensive Language Tasks(2020)
- TransOMCS: From Linguistic Graphs to Commonsense Knowledge(ICJAI 2020)
- Integrating Graph Contextualized Knowledge into Pre-trained Language Models
- Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model (ICLR 2020)
- Language Models as Knowledge Bases?
- KILT: a Benchmark for Knowledge Intensive Language Tasks(2020)
- TransOMCS: From Linguistic Graphs to Commonsense Knowledge(ICJAI 2020)
- Latent Relation Language Models(2019)
- K-BERT: Enabling Language Representation with Knowledge Graph
- K-ADAPTER- Infusing Knowledge into Pre-Trained Models with Adapters
- ERNIE: Enhanced Language Representation with Informative Entities(2019) - Encoder新设计的模块，在该模块中也采用多头注意力机制之后融合编码在分别输出到下一层。]
- Latent Relation Language Models(2019)
- Knowledge Graphs (2020)
- Inducing Relational Knowledge from BERT
- SENSEMBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation
- ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning (AAAI 2019)
- Enriching BERT with Knowledge Graph Embeddings for Document Classification(2019)
- Integrating Graph Contextualized Knowledge into Pre-trained Language Models
- KG-BERT: BERT for Knowledge Graph Completion(2019) - >t,h,r,t->{0,1}的任务特点设计出两个fine-tuning任务。]
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知识计算
- Context-dependent knowledge graph embedding. EMNLP 2015. Luo, Yuanfei and Wang, Quan and Wang, Bin and Guo, Li.
- GAKE: graph aware knowledge embedding. COLING 2016. Feng, Jun and Huang, Minlie and Yang, Yang and Zhu, Xiaoyan.
- KBGAN: Adversarial Learning for Knowledge Graph Embeddings. Cai, Liwei, and William Yang Wang.(NAACL 2018)
- Higher-order Coreference Resolution with Coarse-to-fine Inference (ACL2018)
- Deep Reinforcement Learning for Mention-Ranking Coreference Models (ACL2016)
- KBGAN: Adversarial Learning for Knowledge Graph Embeddings. Cai, Liwei, and William Yang Wang.(NAACL 2018)
- Diachronic Embedding for Temporal Knowledge Graph Completion
- Holographic embeddings of knowledge graphs
- BERT for Coreference Resolution: Baselines and Analysis (2019)
- 指代消解综述 (2010)
- Intra-document Coreference Resolution: The state of the art (2007)
- RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space(ICLR 2019)
- Quaternion Knowledge Graph Embeddings(2019)
- Knowledge Graph Embeddings and Explainable AI(2020)
- Reasoning on Knowledge Graphs with Debate Dynamics
- Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge(2016)
- Differentiable Learning of Logical Rules for Knowledge Base Reasoning.(2017)
- Neural-Symbolic Reasoning on Knowledge Graphs(2020)
- Differentiable Reasoning on Large Knowledge Bases and Natural Language
- Diachronic Embedding for Temporal Knowledge Graph Completion
- Commonsense Knowledge Base Completion with Structural and Semantic Context
- KG-BERT: BERT for Knowledge Graph Completion
- BERT for Coreference Resolution: Baselines and Analysis (2019)
- Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding(NeurIPS 2020)
- Reasoning on Knowledge Graphs with Debate Dynamics
- Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge(2016)
- Differentiable Learning of Logical Rules for Knowledge Base Reasoning.(2017)
- Knowledge Graph Embeddings and Explainable AI(2020)
- RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space(ICLR 2019)
- Commonsense Knowledge Base Completion with Structural and Semantic Context
- KG-BERT: BERT for Knowledge Graph Completion
- Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding(NeurIPS 2020)
- Bootstrapping Entity Alignment with Knowledge Graph Embedding. Zequn Sun, Wei Hu, Qingheng Zhang and Yuzhong Qu.(IJCAI 2018)
- Quaternion Knowledge Graph Embeddings(2019)
- Differentiable Reasoning on Large Knowledge Bases and Natural Language
- Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embeddings(ICLR 2020)
- Neural-Symbolic Reasoning on Knowledge Graphs(2020)
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知识建模
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其他扩展
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知识获取
- Using Type Information to Improve Entity Coreference Resolution
- Zero-shot Entity Linking with Efficient Long Range Sequence Modeling (2020)
- Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
- Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment
- Using Type Information to Improve Entity Coreference Resolution
- Zero-shot Entity Linking with Efficient Long Range Sequence Modeling (2020)
- End-to-End Neural Entity Linking (2018)
- Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment
- Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
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推荐系统
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会议交流及讲座
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图谱及数据集
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领域知识图谱
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数据集
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开放知识图谱
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工具
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机构及人物
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视频课程
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小象学院知识图谱课程
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贪心学院知识图谱课程
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CSDN视频课
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评测竞赛
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CSDN视频课
- 瑞金医院MMC人工智能辅助构建知识图谱大赛
- CCKS 2019 人物关系抽取
- CCKS 2019 中文短文本的实体链指
- CCIR 2019 基于电子病历的数据查询类问答
- CCKS 2019 医疗命名实体识别
- CCKS 2019 公众公司公告信息抽取
- “达观杯”文本智能信息抽取挑战赛
- CCKS 2018 面向音乐领域的命令理解任务
- CCKS 2019 面向金融领域的事件主体抽取
- CCKS 2018 开放领域的中文问答任务
- CCKS 2017 问题命名实体识别和链接任务
- CCKS 2018 面向中文电子病历的命名实体识别
- CCKS 2018 微众银行智能客服问句匹配大赛
- CCKS 2017 面向电子病历的命名实体识别
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推广技术文章
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2020
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2019
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2018
- 知识图谱数据构建的“硬骨头”，阿里工程师如何拿下？
- 为电商而生的知识图谱，如何感应用户需求？
- 知识图谱在旅游领域有哪些应用？携程度假团队这样回答
- 腾讯互娱刘伟：知识图谱让AI更有学识
- 张伟博士：阿里巴巴百亿级别的三元组知识图谱掌舵者
- 知识图谱在互联网金融行业的应用
- 健康知识图谱，阿里工程师如何实现？
- 美团大脑：知识图谱的建模方法及其应用
- 人力资源知识图谱搭建及应用
- 美团餐饮娱乐知识图谱——美团大脑揭秘
- 这是一份通俗易懂的知识图谱技术与应用指南
- 肖仰华谈知识图谱：知识将比数据更重要，得知识者得天下
- 快手结合知识图谱进行多模态内容理解
- 腾讯互娱刘伟：知识图谱让AI更有学识
- 基于概念知识图谱的短文本理解——王仲远
- 上交大发布知识图谱AceKG，超1亿实体，近100G数据量
- 一文揭秘！自底向上构建知识图谱全过程
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2017
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项目案例
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金融领域知识图谱
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