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Grant Ingersoll commented on LUCENE-2091: ----------------------------------------- I haven't looked at the patch yet, but... Should we take just a small step back and consider what it would take to actually make scoring more pluggable instead of just thinking about how best to integrate BM25? In other words, someone else has also donated an implementation of the Axiomatic Retr. Function. Much like BM25, I think it also requires avg. doc length, as does (I believe) language modeling and some other approaches. Of course, we need to do this in a way that doesn't hurt performance for the default case. I'm also curious if anyone has compared BM25 w/ a Lucene similarity that uses a different length normalization factor? I've seen many people use a different len. norm with good success, but it isn't necessarily for everyone. > Add BM25 Scoring to Lucene > -------------------------- > > Key: LUCENE-2091 > URL: https://issues.apache.org/jira/browse/LUCENE-2091 > Project: Lucene - Java > Issue Type: New Feature > Components: contrib/* > Reporter: Yuval Feinstein > Priority: Minor > Fix For: 3.1 > > Attachments: LUCENE-2091.patch, persianlucene.jpg > > Original Estimate: 48h > Remaining Estimate: 48h > > http://nlp.uned.es/~jperezi/Lucene-BM25/ describes an implementation of > Okapi-BM25 scoring in the Lucene framework, > as an alternative to the standard Lucene scoring (which is a version of mixed > boolean/TFIDF). > I have refactored this a bit, added unit tests and improved the runtime > somewhat. > I would like to contribute the code to Lucene under contrib. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online. --------------------------------------------------------------------- To unsubscribe, e-mail: java-dev-unsubscr...@lucene.apache.org For additional commands, e-mail: java-dev-h...@lucene.apache.org