Hello, I'd like to score documents higher that have the user's search terms nearer each other. For example, if a user searches for
a AND b AND c the standard query handler should return all documents with [a] [b] and [c] in them, but documents matching the phrase "a b c" should get a boost over those with "a x b c" over those with "b x y c z a", etc. To accomplish this, I thought I might replace the user's query with "a b c"~1000000000 hoping that the slop term gets a higher and higher score the closer together [a] [b] and [c] appear. This doesn't seem to be the case in my experiments; when I debug the query, there's no component of the score based on how close together [a] [b] and [c] are. And I'm suspicious that this would make my queries a whole lot slower -- in reality my users' queries get expanded quite a bit already, and I'd thus need to add many slop terms. Perhaps instead I could modify the Standard query handler to examine the distance between all ANDed tokens, and boost proportionally to the inverse of their average distance apart. I've never modified a query handler before so I have no idea if this is possible. Any suggestions on what approach I should take? The less I have to modify Solr, the better -- I'd prefer a query-side solution over writing a plugin over forking the standard query handler. Thanks in advance! Michael
