I'd like to have suggestions on changing the scoring algorithm
of MoreLikeThis.
When I feed the identical string as the content of a document in the index
to MoreLikeThis.like("field", new StringReader(docContent)),
I get a score less than 1.0 (0.944 in one of my test cases) that I expect.
What is the easiest way to change this so that the score is 1.0 when
all the terms in the query matches with all the terms of a document?
The score should be less than 1.0 if the query contains only a part of the terms
from the document. (Needless to say, the score should also be less than 1.0
if only part of the query terms are found in the document.)
For my purpose, I don't need a sophisticated search relevancy technique
like TF-IDF. I'd like it work faster/cheaper.
I tried using BooleanSimilarity, but that ended up returning a score above 1.0.
Also the score is the same as long as all the terms in the query are matched.
For example, querying "quick brown fox" and "quick brown" yield the same score
against
the doc that has the famous test string.
TK
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