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https://issues.apache.org/jira/browse/LUCENE-3290?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13062363#comment-13062363
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Robert Muir commented on LUCENE-3290:
-------------------------------------
Just more explanation, there are two parts to the patch:
# FieldInvertState gets an additional variable, numUniqueTerms. its not stored
anywhere. this just allows you to use this as part of your
Similarity.computeNorm calculation, if you like.
# in trunk *only* we store sumDocFreq, which changes the index format. but this
is not easy to backport to 3.x, as fields are not clearly separated (which
would make it a little tricky), and its missing new stats anyway like
totalTermFreq (because it would bloat TermInfos).
> add FieldInvertState.numUniqueTerms, Terms.sumDocFreq
> -----------------------------------------------------
>
> Key: LUCENE-3290
> URL: https://issues.apache.org/jira/browse/LUCENE-3290
> Project: Lucene - Java
> Issue Type: Improvement
> Components: core/index
> Reporter: Robert Muir
> Assignee: Robert Muir
> Fix For: 3.4, 4.0
>
> Attachments: LUCENE-3290.patch, LUCENE-3290.patch
>
>
> For scoring systems like lnu.ltc
> (http://trec.nist.gov/pubs/trec16/papers/ibm-haifa.mq.final.pdf), we need to
> supply 3 stats:
> * average tf within d
> * # of unique terms within d
> * average number of unique terms across field
> If we add FieldInvertState.numUniqueTerms, you can incorporate the first two
> into your norms/docvalues (once we cut over),
> the average tf within d being length / numUniqueTerms.
> to compute the average across the field, we can just write the sum of all
> terms' docfreqs into the terms dictionary header,
> and you can then divide this by maxdoc to get the average.
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