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From "Michael McCandless (JIRA)" <>
Subject [jira] [Commented] (LUCENE-5354) Blended score in AnalyzingInfixSuggester
Date Mon, 02 Dec 2013 14:57:39 GMT


Michael McCandless commented on LUCENE-5354:

This sounds very useful!

I think a subclass could work well, if we open up the necessary methods (which Query to run,
how to do the search / resort the results)?

We could make the index-time sorting optional as well?  This way you'd build an "ordinary"
index, run an "ordinary" query, so you have full flexibility (but at more search-time cost).

> Blended score in AnalyzingInfixSuggester
> ----------------------------------------
>                 Key: LUCENE-5354
>                 URL:
>             Project: Lucene - Core
>          Issue Type: Improvement
>          Components: modules/spellchecker
>    Affects Versions: 4.4
>            Reporter: Remi Melisson
>            Priority: Minor
>              Labels: suggester
> 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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