Flexible ranking in Lucene 4

Flexible ranking in Lucene 4

Robert Muir writes:

Over the summer I served as a Google Summer of Code mentor for David Nemeskey, PhD student at Eötvös Loránd University. David proposed to improve Lucene’s scoring architecture and implement some state-of-the-art ranking models with the new framework.

These improvements are now committed to Lucene’s trunk: you can use these models in tandem with all of Lucene’s features (boosts, slops, explanations, etc) and queries (term, phrase, spans, etc). A JIRA issue has been created to make it easy to use these models from Solr’s schema.xml.

Relevance ranking is the heart of the search engine, and I hope the additional models and flexibility will improve the user experience for Lucene: whether you’ve been frustrated with tuning TF/IDF weights and find an alternative model works better for your case, found it difficult to integrate custom logic that your application needs, or just want to experiment.

The wiki page for this project has a pointer to the search engine in A “Terrier” For Your Tool Box?.

I count a baker’s dozen or so new features described in this post.

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