Hi Michael, Using your example, if you have 5 different fields, you could create 5 individual SolrFeatures against those fields. The one tricky thing here is that you want to use different similarity scoring mechanisms against your fields. By default, Solr uses a single Similarity class <https://lucene.apache.org/core/6_1_0/core/org/apache/lucene/search/similarities/Similarity.html> against your fields to rank all your documents. However, you could define new types for your special title & description fields that use different Similarity classes <https://cwiki.apache.org/confluence/display/solr/Other+Schema+Elements>. This is an interesting approach and seems like it could solve your problem.
Hope that helps -Mike On Fri, Aug 4, 2017 at 10:18 AM, Michael Alcorn <malc...@redhat.com> wrote: > Hi all, > > I recently prototyped a learning to rank system in Python that produced > promising results, so I'm now looking into how to replicate that process in > our Solr setup. For my Python implementation, I was using a number of > features that were per field text comparisons, e.g.: > > 1. tfidf_case_title_solution_title > 2. tfidf_case_description_solution_title > 3. ... > 4. bm25_case_title_solution_description > 5. bm25_case_description_solution_description > > where each solution field had its own independent index. I was wondering if > any of you all had recommendations on how to do that type of thing in Solr. > It looks like the SolrFeature class might be the way to go, but my > colleagues who are more familiar with Solr than I am weren't sure it was > possible. > > Thanks, > Michael A. Alcorn >
