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Mark Miller commented on LUCENE-1908: ------------------------------------- bq. In that work we got best results from Lucene Thats funny - I didn't notice you were an author one that one! Small world. The original idea of why the cosine normalization for the doc vector is bad, I got from the free intro to info retrieval book thats out there - but what it says doesn't fully jive with the info I am finding elsewhere, or my own common sense. Thats what has me most confused at the moment - the intro to ir book appears to break it down so that you can explain it with the math (why going into the unit vector space favors longer docs) - but other work I am seeing says the math tells you no such thing, and its just comparing it to the computed relevancy curve that tells you its not great. I dunno :) - though at least I know a lot more than I did a few days ago - it never even occurred to me how the scoring we did equated to any kind of dot product before this - I used to read Lucene's scoring algorithm and then look at the code and it was like .... okay - sure ... - so I've come a long way. > Similarity javadocs for scoring function to relate more tightly to scoring > models in effect > ------------------------------------------------------------------------------------------- > > Key: LUCENE-1908 > URL: https://issues.apache.org/jira/browse/LUCENE-1908 > Project: Lucene - Java > Issue Type: Improvement > Components: Search > Reporter: Doron Cohen > Assignee: Doron Cohen > Priority: Minor > Fix For: 2.9 > > Attachments: LUCENE-1908.patch, LUCENE-1908.patch > > > See discussion in the related issue. -- 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