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https://issues.apache.org/jira/browse/LUCENE-2091?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12786164#action_12786164
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Grant Ingersoll commented on LUCENE-2091:
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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.
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