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From "Remi Melisson (JIRA)" <j...@apache.org>
Subject [jira] [Created] (LUCENE-5354) Blended score in AnalyzingInfixSuggester
Date Mon, 02 Dec 2013 12:19:36 GMT
Remi Melisson created LUCENE-5354:
-------------------------------------

             Summary: Blended score in AnalyzingInfixSuggester
                 Key: LUCENE-5354
                 URL: https://issues.apache.org/jira/browse/LUCENE-5354
             Project: Lucene - Core
          Issue Type: Improvement
          Components: modules/spellchecker
    Affects Versions: 4.4
            Reporter: Remi Melisson
            Priority: Minor


I'm working on a custom suggester derived from the AnalyzingInfix. I require what is called
a "blended score" (//TODO ln.399 in AnalyzingInfixSuggester) to transform the suggestion weights
depending on the position of the searched term(s) in the text.

Right now, I'm using an easy solution :
If I want 10 suggestions, then I search against the current ordered index for the 100 first
results and transform the weight :
bq. a) by using the term position in the text (found with TermVector and DocsAndPositionsEnum)
or
bq. b) by multiplying the weight by the score of a SpanQuery that I add when searching
and return the updated 10 most weighted suggestions.

Since we usually don't need to suggest so many things, the bigger search + rescoring overhead
is not so significant but I agree that this is not the most elegant solution.
We could include this factor (here the position of the term) directly into the index.

So, I can contribute to this if you think it's worth adding it.

Do you think I should tweak AnalyzingInfixSuggester, subclass it or create a dedicated class
?




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