Yes, you can use DFISimilarity with an index constructed with
BM25Similarity. No need to reindex.
On Fri, Jun 14, 2019 at 1:05 PM Frédéric Glorieux <emp...@fictif.org> wrote:
>
> Hi,
>
> I'm working on literature texts (French).
>
> My users are interested in relevance tweaking to have the most suggested
> texts (for their taste) in top results.
>
> Change similarity at query time is less expensive than reindex all.
>
> I checked that BM25 needs to write “norms“ to keep document length.
>
> Have I missed something ? DFISimilarity seems to write and use norms
> from SimilarityBase, where it is written
>
> computeNorms «Encodes the document length in the same way as {@link
> BM25Similarity}»
>
> For my first experiences, it seems that results with DFISimilarity at
> query time are the same with an index encoded with default
> BM25Similarity or DFI.
>
> Can some gurus confirm with their experience ?
>
> Thanks in advance (and lucene is really a good piece of software).
>
> --
> Frédéric
>
>
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Adrien
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