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From Simon Svensson <>
Subject Re: Getting fuzzy match information
Date Thu, 12 Dec 2013 16:42:56 GMT

I feel that is 
somewhat relevant, even if you're not strictly talking about normalizing 
your scores.

I would look into calling indexSearcher.Explain(Query query, Int32 
docId) to retrieve an Explanation object that _should_ container 
information how your document matched, including scores for every term. 
(The actual user interface for presenting this is left to the reader. 

// Simon

On 12/12/13 17:22, Allan, Brad (Bracknell) wrote:
> Has anyone done or know of work done that would help me to get detailed information about
my hits with regard to fuzzy matches? Also very happy to receive suggestions :).
> I'm looking to obtain the similarity percentage of each token in the each hit.
> Example: fuzzy query looks something like this:
> (name:80% similar to "john" or name:80% similar to "henry" or name:80% similar to "smith")
> And I get hits:
> *         Jon George Smythe
> *         John Joe Henry
> *         Smith John & Carter engineering
> All valid hits, however my users want to be able to view the similarity and indeed prioritise
certain actions by being able to compare the results of 2 different searches (and therefore
normalised scores are not as useful as knowing the actual similarity information).
> Clearly this sort of ability does not make sense when one is searching in large amounts
of data (documents), but in my case I'm searching through a set of names and some additional
person information.
> Options could be to post process the hits and use/lift the FuzzyTermEnum logic to re-compute
the similarity value. Or perhaps extend the FuzzyQuery to register a 'listener' to receive
the information?
> Other ideas? Thoughts?
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