o19s/elasticsearch-learning-to-rank
Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch observed · 2026-08-28
Health v2 · maintenance only
90/100
- Activity 87
- Release rhythm 89
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 9.5
- age_days: 3538
- days_rel: 78
- days_push: 78
- n_releases_24m: 17
Adoption not part of the score
1521 stars · 372 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
An Elasticsearch plugin that integrates Learning to Rank (machine-learned relevance) into Elasticsearch. It stores feature query templates, logs feature scores for training set creation, and applies stored linear, XGBoost, or RankLib models to rerank search results.
Use cases
- improve search relevance ranking with machine learning in elasticsearch
- train a learning-to-rank model for my search engine
- rerank elasticsearch results using xgboost
- log feature scores to build a training set for search relevance
- store and deploy ranking models in elasticsearch
- replace manual relevance tuning with automated ranking
When to choose
- you run Elasticsearch and want ML-driven relevance instead of manual boost tuning
- you have click/judgment data to train ranking models offline
- you need feature logging to build training sets from query templates
When to avoid
- you use OpenSearch or Solr rather than Elasticsearch (though a Solr LTR exists)
- you need vector/neural semantic search rather than feature-based LTR
- you cannot operate offline model training pipelines
Facets
plugin · maturity active
search-engine machine-learning plugin-system machine-learning developer-tools jvm self-hosted elasticsearch-plugin learning-to-rank search-relevance ltr xgboost ranklib search
8 sources
- readme: https://github.com/o19s/elasticsearch-learning-to-rank · fetched 2026-08-28 · 3604443ca732
- homepage: http://opensourceconnections.com/blog/2017/02/14/elasticsearch-learning-to-rank/ · fetched 2026-08-29 · a912c1c893dc
- site_page: https://opensourceconnections.com/about-us · fetched 2026-08-29 · 1f2c9b427d52
- site_page: https://opensourceconnections.com/about-us/careers-eu · fetched 2026-08-29 · 181bc53f9eba
- site_page: https://opensourceconnections.com/about-us/careers · fetched 2026-08-29 · 1c35ee569f3a
- site_page: https://opensourceconnections.com/about-us/books-resources · fetched 2026-08-29 · 858bf2655425
- site_page: https://opensourceconnections.com/about-us/tools · fetched 2026-08-29 · 26120bbbf338
- site_page: https://opensourceconnections.com/about-us/videos-about-search · fetched 2026-08-29 · 34acf57d4dda
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| o19s/elasticsearch-learning-to-rank | main | 90 |
For agents
markdown · JSON · MCP: product_card(name="o19s/elasticsearch-learning-to-rank")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem