On 5/30/07, Walt Stoneburner <[EMAIL PROTECTED]> wrote:
a) Where does freq come from? (Not what is it, but who computes it and how?)
For a single term, it's determined at index time and stored in the index. TermDocs gives you a list of documents containing the term, and for each document, the number of time the term appears (the freq). Note: TermScorer calls the tf(int) version on Similarity rather than the tf(float) version.
c) What values should I be passing out of a function like this? Should I normalize my outgoing scores to some scale, or do I simply just need to provide numbers that "have the right shaped curve".
Hits normalizes to 1 based on the max score, if that max score is greater than 1. Scores across queries aren't really comparable though.
I look at things like idf() which returns 1+log(ratio) and then has that value squared. Clearly that isn't on a scale of 1.0 to 0.0. I feel like there may be some mathematical trickery going on and that maybe the actual score values themselves don't matter inside the ranking code, so long as their relative values to one another.
Pretty much.
This then makes me ponder how the normalization process is done between queries, allowing for a mix'n'match of results as these numbers spill to the outside world. Obviously normalization has to happen at that point for the mixing query results magic to work.
Lucene doesn't currently do this "mixing", and it's not really clear to me how it should be done. -Yonik --------------------------------------------------------------------- To unsubscribe, e-mail: [EMAIL PROTECTED] For additional commands, e-mail: [EMAIL PROTECTED]
