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 <j...@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 > > > > --------------------------------------------------------------------- > To unsubscribe, e-mail: java-user-unsubscr...@lucene.apache.org > For additional commands, e-mail: java-user-h...@lucene.apache.org > > --------------------------------------------------------------------- To unsubscribe, e-mail: java-user-unsubscr...@lucene.apache.org For additional commands, e-mail: java-user-h...@lucene.apache.org
