I've never really tackled anything like this, but a few things to consider / watch out for are:
1) if a doc *only* matches because of the negated field do you really want to consider it a match? Even in the case of dismax, the minNrShouldMatch aspect is going to is going to consider your megation field a factor, so you might find documents being considered a match, even though they don't contain enough of the input terms in "normal" fields because some terms are in the negated field. 2) the coord factor might wind up throwing your scores off in weird ways ... something that matches on the title, the content, and the negation field could wind up scoring higher then something that matches only on title and content because of coord. There's a "BoostingQuery" in the Lucene queries contrib that (in theory) helps with some of this by rewriting to a BooleanQuery with a custom coord function, but i'v never looked at it closely. : I'm working on a case where we have review text that may include words that : describe what the item is *not*. : : Given the text "the kitten is not clean", searching for "clean" should not : include (at least at the top) the kitten. : : The approach I am considering is to copy the text to a negation field and do : simple heuristic analysis in a TokenFilter. This analysis would only keep : tokens for words that follow "not", then we could add a negative boost for : this field: : title^2 content^1 negation^0.1 : : Does this seem like a reasonable approach? Any other ideas / suggestions / : pointers? -Hoss
