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https://issues.apache.org/jira/browse/LUCENE-2091?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12786207#action_12786207
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Robert Muir commented on LUCENE-2091:
-------------------------------------
bq. In other words, someone else has also donated an implementation of the
Axiomatic Retr. Function.
I've never been able to get that scoring function to do anything more than be
consistently worse than the default Lucene formula. I tried at least 3 test
collections with it...
bq. 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.
Yes in the image posted here, I tried modifying length normalization with
SweetSpot etc as others have done in the past. For this corpus I was unable to
improve it in this way.
But maybe I made some mistakes in both these cases, so anyone feel free to try
this themselves.
> 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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