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From "Bauer, Herbert S. (Scott)" <>
Subject Re: Scoring over Multiple Indexes
Date Thu, 22 Oct 2015 18:29:57 GMT
Thanks for your reply.  We¹ve recently moved from a single large index to
multiple indexes. Given that the content loaded for these indexes
represents individually curated terminologies, I think we can argue to our
users that what comes from combined queries over the latter is as
meaningful in it¹s own right as those run over the monolithic index. We
had to consider that our changes to the back end of our application might
change sorting orders for results which is what we normally want to avoid.

On 10/22/15, 10:43 AM, "Erick Erickson" <> wrote:

>In a word, no. At least not that I've heard of. "normalizing scores"
>is one of those things
>that sounds reasonable on the surface, but is really meaningless.
>Scores don't really
>_tell_ you anything about the abstract "goodness" of a doc, they just
>tell you that
>doc1 is likely better than doc2 _within a single query_. You can't even
>scores in the _same_ index across two different queries.
>At its lowest level, say one index has 1,000,000 occurrences of
>"erick", while index 2 has
>exactly 1. Term frequency is one of the numbers that is used to
>calculate the score.
>How does one normalize the part of the calculation resulting from
>matching "erick"
>between the two indexes? Anything you do is wrong.
>Similarly, expecting documents to be returned in a particular order
>because of boosting
>is not going to be satisfactory. Boosting will influence the final
>score and thus the
>position of the document, but not absolutely order them unless you put
>in insane boosts.
>Tests based on boosting and doc ordering will be very fragile I'd guess.
>On Thu, Oct 22, 2015 at 8:34 AM, Bauer, Herbert S. (Scott)
><> wrote:
>> We have a test case that boosts a set of terms.  Something along the
>>lines of ³term1^2 AND term2^3 AND term3^4 and this query runs over a two
>>content distinct indexes.  Our expectation is that the terms would be
>>returned to us as term3, term2 and term1.  Instead we get something
>>along the lines of term3, term1 and term2.  I realize from a number of
>>postings that this is the result of the scoring methods action taking
>>place within an individual index rather than against several indexes.
>>At the same time I don¹t see a lot of solutions offered. Is there an out
>>of the box solution to normalize scoring over diverse indexes?  If not
>>is there a strategy for rolling your own normalizing solution?  I¹m
>>assuming this has to be a common problem.    -scott
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