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From Babak Farhang <farh...@gmail.com>
Subject Re: relevance function for scores
Date Mon, 25 May 2009 22:10:10 GMT
How about determining the cutoff by measuring the percentage
difference between successive scores: if the score drops by a
threshold amount then you've hit the cutoff.  In the example you
mention, you might want to try something like c/1000, where 1 < c < 25
is a constant (experiment to find a sweet spot for c).

I.e. something like

if (score[n-1]  / score[n)  < c / (boost_factor) ,

then you've reached your cutoff at the n-1th hit
(where boost_factor=1000 in your example).

One thing to check is that the scores are indeed sorted in descending
order to begin with.  For example, I don't think the hits in
TopDocCollector and its brethren are strictly ordered this way (no?).

-Babak

On Mon, May 18, 2009 at 6:52 AM, Joel Halbert <joel@su3analytics.com> wrote:
> Hi,
>
> I'd like to apply a score filter. I realise that filtering by absolute
> (i.e. anything less than x) scores is pretty meaningless.
>
> In my case I want to filter based on relative score - or on some
> function of score which looks for clustering of documents around certain
> score values.
>
> Context: I have set up field boosts such that a query hit on one indexed
> field will, in theory, result in a score one or more order of magnitudes
> greater than a hit on some other field. So if I have 2 fields A and B
> and I'm really really interested in hits on A, and only interested in
> hits on B if there were none on A,  I boost A by 1000, relative to B.
> The resultant score should reflect this.
>
> The ability to do this becomes important when we want to re-order the
> search results around some other field (not score) and are not
> interested in displaying the least relevant documents.
>
>
> It is an easy thing to write a basic 'document collector/result filter'
> that uses relative score information to filter out documents where any
> score is less than some magnitude of the best score, but I'm sure this
> could be more elegantly generalised into some mathematical
> "relevance/significance" model/function  which could determine some
> optimal cutoff for documents based on the clustering of results around
> scores.
> e.g. if my top 5 documents are all between score 0.9 and 0.7 and the
> remaining 10 are less than 0.01 then we could sensibly take the top 5
> docs as most relevant.
>
> Has anyone experience of doing such a thing?
>
>
> Regards,
> Joel
>
>
>
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