{"id":13467178,"url":"https://github.com/o19s/elasticsearch-learning-to-rank","last_synced_at":"2025-05-14T07:09:41.937Z","repository":{"id":15221322,"uuid":"77308564","full_name":"o19s/elasticsearch-learning-to-rank","owner":"o19s","description":"Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch","archived":false,"fork":false,"pushed_at":"2025-03-11T16:08:48.000Z","size":2204,"stargazers_count":1497,"open_issues_count":38,"forks_count":370,"subscribers_count":69,"default_branch":"main","last_synced_at":"2025-04-11T22:19:37.413Z","etag":null,"topics":["elasticsearch","elasticsearch-plugin","elasticsearch-plugins","machine-learning","relevant-search","search-relevance"],"latest_commit_sha":null,"homepage":"http://opensourceconnections.com/blog/2017/02/14/elasticsearch-learning-to-rank/","language":"Java","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/o19s.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2016-12-25T03:19:01.000Z","updated_at":"2025-04-09T05:27:11.000Z","dependencies_parsed_at":"2023-12-13T16:31:43.870Z","dependency_job_id":"6b11f2ee-d9d2-401f-9e7e-9e8f8f557fe3","html_url":"https://github.com/o19s/elasticsearch-learning-to-rank","commit_stats":null,"previous_names":[],"tags_count":76,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o19s%2Felasticsearch-learning-to-rank","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o19s%2Felasticsearch-learning-to-rank/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o19s%2Felasticsearch-learning-to-rank/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o19s%2Felasticsearch-learning-to-rank/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/o19s","download_url":"https://codeload.github.com/o19s/elasticsearch-learning-to-rank/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254092788,"owners_count":22013290,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["elasticsearch","elasticsearch-plugin","elasticsearch-plugins","machine-learning","relevant-search","search-relevance"],"created_at":"2024-07-31T15:00:53.853Z","updated_at":"2025-05-14T07:09:36.929Z","avatar_url":"https://github.com/o19s.png","language":"Java","funding_links":[],"categories":["Java","人工智能","Elasticsearch"],"sub_categories":["Tools"],"readme":"[![Build Status](https://travis-ci.com/o19s/elasticsearch-learning-to-rank.svg?branch=master)](https://travis-ci.com/o19s/elasticsearch-learning-to-rank)\n\nThe Elasticsearch Learning to Rank plugin uses machine learning to improve search relevance ranking. It's powering search at places like Wikimedia Foundation and Snagajob!\n\n# What this plugin does...\n\nThis plugin:\n\n- Allows you to store features (Elasticsearch query templates) in Elasticsearch\n- Logs features scores (relevance scores) to create a training set for offline model development\n- Stores linear, xgboost, or ranklib ranking models in Elasticsearch that use features you've stored\n- Ranks search results using a stored model\n\n## Where's the docs?\n\nWe recommend taking time to [read the docs](http://elasticsearch-learning-to-rank.readthedocs.io). There's quite a bit of detailed information about learning to rank basics and how this plugin can ease learning to rank development. \n\nYou can also participate in regular [trainings](http://opensourceconnections.com/events/training) on Elasticsearch Learning to Rank, which support the free work done on this plugin.\n\n## I want to jump in!\n\nThe demo lives in another repo now, [Hello LTR](https://github.com/o19s/hello-ltr) and it has both ES and Solr example. Follow the directions for Elasticsearch in the README to set up the environment and start with the [notebooks/elasticsearch/tmdb/hello-ltr.ipynb](https://github.com/o19s/hello-ltr/blob/master/notebooks/elasticsearch/tmdb/hello-ltr%20(ES).ipynb). Have fun!\n\n# Installing\n\nSee the full list of [prebuilt versions](https://github.com/o19s/elasticsearch-learning-to-rank/releases) and select the version that matches your Elasticsearch version. If you don't see a version available, see the link below for building or file a request via [issues](https://github.com/o19s/elasticsearch-learning-to-rank/issues).\n\nTo install, you'd run a command like this but replacing with the appropriate prebuilt version zip:\n\n`./bin/elasticsearch-plugin install https://github.com/o19s/elasticsearch-learning-to-rank/releases/download/v1.5.4-es7.11.2/ltr-plugin-v1.5.4-es7.11.2.zip`\n\n(It's expected you'll confirm some security exceptions, you can pass `-b` to `elasticsearch-plugin` to automatically install)\n\nIf you already are running Elasticsearch, don't forget to restart!\n\n# Known issues\nAs any other piece of software, this plugin is not exempt from issues. Please read the [known issues](KNOWN_ISSUES.md) to learn about the current issues that we are aware of. This file might include workarounds to mitigate them when possible.\n\n# Build and Deploy Locally\n\nNotes if you want to dig into the code or build for a version there's no build for, please feel free to run the build and installation process yourself:\n\n```\n./gradlew clean check\n./bin/elasticsearch-plugin install file:///path/to/elasticsearch-learning-to-rank/build/distributions/ltr-\u003cLTR-VER\u003e-es\u003cES-VER\u003e.zip\n```\n\n# How to Contribute\n\nFor more information on helping us out (we need your help!), developing with the plugin, creating docs, etc please read [CONTRIBUTING.md](/CONTRIBUTING.md).\n\n## Elastic Release Support\nWe do our best to officially support `*.*.1` releases of Elasticsearch.  If you have a need for \"dot-oh\" compatibility or a version we don't support please consider submitting a PR.\n\n \n# Who built this?\n- [Initially developed](http://opensourceconnections.com/blog/2017/02/14/elasticsearch-learning-to-rank/) at [OpenSource Connections](http://opensourceconnections.com).\n- Significant contributions by [Wikimedia Foundation](https://wikimediafoundation.org/wiki/Home), [Snagajob Engineering](https://engineering.snagajob.com/), [Bonsai](https://bonsai.io/), and [Yelp Engineering](https://engineeringblog.yelp.com/)\n- Thanks to [Jettro Coenradie](https://amsterdam.luminis.eu/author/jettro/) for porting to ES 6.1\n\n## Other Acknowledgments \u0026 Stuff To Read\n- Bloomberg's [Learning to Rank work for Solr](https://issues.apache.org/jira/browse/SOLR-8542)\n- Our Berlin Buzzwords Talk, [We built an Elasticsearch Learning to Rank plugin. Then came the hard part](https://2017.berlinbuzzwords.de/17/session/we-built-elasticsearch-learning-rank-plugin-then-came-hard-part.html)\n- Blog article on [How is Search Different from Other Machine Learning Problems](http://opensourceconnections.com/blog/2017/08/03/search-as-machine-learning-prob/)\n- Also check out our other relevance/search thingies: book [Relevant Search](http://manning.com/books/relevant-search), projects [Elyzer](http://github.com/o19s/elyzer), [Splainer](http://splainer.io), and [Quepid](http://quepid.com)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fo19s%2Felasticsearch-learning-to-rank","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fo19s%2Felasticsearch-learning-to-rank","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fo19s%2Felasticsearch-learning-to-rank/lists"}