Hi John, A TermQuery produces a scorer that can compute similarity for a given term value against a given field, in the context of the index, so as you say, it produces a score for one field.
If you want to match a given term value across multiple fields, indeed you could use a BooleanQuery with the TermQueries in SHOULD clauses. The vanilla BooleanQuery produces a score which is the sum of all matching clauses' scores (or at least that's the interpretation I get from reading the source code of the explain() method in BooleanWeight). You can also look into DisjunctionMaxQuery, which works like a disjunctive BooleanQuery, but it returns the maximum score across matching clauses. The idea here is that if, say, you're matching across title and body fields, a title match may score higher (perhaps because it's been boosted). If you sum the scores across fields, you're likely just inflating those title matches even more (since a title match is probably highly correlated with a body match). (The DisjunctionMaxQuery also has a an optional "tieBreakerMultiplier" property that you can use to weight the scoring somewhere between pure max and pure sum -- like "Use the maximum score, plus 0.001 times the sum of the rest".) Hope that helps, Michael On Mon, 27 Jan 2020 at 13:37, John Brown <brown.j...@temple.edu> wrote: > Hi, > > I have a question regarding how Lucene computes document similarities from > field similarities. > > Lucene's scoring documentation mentions that scoring works on fields and > combines the results to return documents. I'm assuming fields are given > scores, and those scores are simply averaged to return the document score? > > If this is the case, then in order to incorporate multiple fields in my > scoring, I would use multiple term queries that contain the same term, but > target different fields, then I would simply put them in a boolean query, > and search my index using this boolean query. > > Am I going about this in the correct way? Any clarification would be > greatly appreciated. > > Thank you, > John B >
