Thank you for your answer, but please could you explain this idea in
detail as I cannot see how this would help solving my problem?
For example, I got the indexed Wikipedia Article "Alan Smithee" with a
document length of 756, which also is used when calculating the average
document length. But if the BM25 score in this article is calculated it
uses the approximated document length of 728, which returns a different
result from when the score is calculated with the correct document
length. So I wonder where this value is calculated and how I might
change this approximation or at least can get the approximated value, so
that I can use it for my own calculations.
On 2020-06-02 18:48, Michael Sokolov wrote:
You could append an EOF token to every indexed text, and then iterate
over Terms to get the positions of those tokens?
On Tue, Jun 2, 2020 at 11:50 AM Moritz Staudinger
<mor...@staudinger.work> wrote:
Hello,
I am not sure if I am at the right place here, but I got a question
about
the approximation my Lucene implementation does.
I am trying to calculate the same scores Lucenes BM25Similiarity
calculates,
but I found out that Lucene only approximates the length of documents
for
scoring but uses the correct values for the average document length.
Is there a way to turn off these approximations or to get the values,
so
that I can save it for my own calculations?
For my Implementation I use Lucene 8.4.1 in Combination with Spring
Boot, if
this is necessary.
Thank you in advance,
Moritz
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