Hi David, It may not matter for your use case but just in case you really are interested in the "real BM25F" there is a difference between configuring K1 and B for different fields in Solr and a "real" BM25F implementation. This has to do with Solr's model of fields being mini-documents (i.e. each field has its own length, idf and tf) See the discussion in https://issues.apache.org/jira/browse/LUCENE-2959, particularly these comments by Robert Muir:
"Actually as far as BM25f, this one presents a few challenges (some already discussed on LUCENE-2091 <https://issues.apache.org/jira/browse/LUCENE-2091> ). To summarize: - for any field, Lucene has a per-field terms dictionary that contains that term's docFreq. To compute BM25f's IDF method would be challenging, because it wants a docFreq "across all the fields". (its not clear to me at a glance either from the original paper, if this should be across only the fields in the query, across all the fields in the document, and if a "static" schema is implied in this scoring system (in lucene document 1 can have 3 fields and document 2 can have 40 different ones, even with different properties). - the same issue applies to length normalization, lucene has a "field length" but really no concept of document length." Tom On Thu, Apr 14, 2016 at 12:41 PM, David Cawley <david.cawl...@mail.dcu.ie> wrote: > Hello, > I am developing an enterprise search engine for a project and I was hoping > to implement BM25F ranking algorithm to configure the tuning parameters on > a per field basis. I understand BM25 similarity is now supported in Solr > but I was hoping to be able to configure k1 and b for different fields such > as title, description, anchor etc, as they are structured documents. > I am fairly new to Solr so any help would be appreciated. If this is > possible or any steps as to how I can go about implementing this it would > be greatly appreciated. > > Regards, > > David > > Current Solr Version 5.4.1 >
