Hi Ajinkya, I don't think there exists any production-ready LtR-Lucene/Solr setup.
LtR simply re-rank top N (typically 1000) documents. Fetching top N documents is what we do today with Lucene. There is an API for re-rank in Lucene/Solr but no LtR support yet. https://cwiki.apache.org/confluence/display/solr/Query+Re-Ranking Here are the difficulties/problems : * LtR requires training data (probably labelled by humans) * It is hard to decide the feature set. Also it differs from system to system. * Query-dependeny features must be calculated for the top N documents at query/retrieval time, which may be slow. Today, generally function queries are used to combine recency, popularity, star, product/document quality, price, etc into scoring function. This approach is unsupervised therefore requires no training data. Ahmet On Tuesday, August 18, 2015 10:34 AM, Ajinkya Kale <kaleajin...@gmail.com> wrote: Are there any existing packages/examples or prior experience on using Learning to Rank (or Machine Learned Ranking) algorithms as custom Scorer/Ranker for lucene or solr ? How do people deploy Learning to Rank models with Lucene backends ? --ajinkya --------------------------------------------------------------------- To unsubscribe, e-mail: java-user-unsubscr...@lucene.apache.org For additional commands, e-mail: java-user-h...@lucene.apache.org
