Doug, thanks for a quick response.
If I understand it correctly, the answer to my next question is "no",
but still,
Are the weights at least bounded or can they potentially be any float?
Also, when the new field and document boosts are incorporated, how
does this change the picture?
Thanks again.
Dmitry.
Doug Cutting wrote:
> Dmitry Serebrennikov wrote:
>
>> I know that the FAQ says that they are, but in at least one instance
>> in my index it appears to be equal to 1.94something. Are the scores
>> guaranteed to be between 0 and 1
>
>
> No.
>
> > and if not, what would it take to make
>
>> them such?
>
>
> A different Similarity implementation.
>
> To do this right you need to divide each document's score by the
> square root of the sum of all of the document's term weights. This is
> hard to do, since the term weights depend on each term's document
> frequency and hence change when documents are added and deleted from
> the index. Thus this denominator would have to be recomputed for
> every document each time the index changes. Or you could use term
> weights that don't depend on document frequency, or ...
>
> Doug
>
>
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