from all the examples of what you've described, i'm fairly certain all you
really need is a TFIDF based Similarity where coord(), idf(), tf() and
queryNorm() return 1 allways, and you omitNorms from all fields.
Yeah, that's what I did in the very first iteration. It works only for
cases #1 and
: 1. name:DocumentOne^7 => doc1(score=7)
: 2. name:DocumentOne^7 AND place:notExist^3 => doc1(score=7)
: 3. place:(34\ High\ Street)^3 => doc1(score=3), doc2(score=3)
: 4. name:DocumentOne^7 OR place:(34\ High\ Street)^3 => doc1(score=10),
: doc2(score=3)
...
: > it's not clear why you nee
how are you defining/specifying these field weights?
I define weights inside of a query (name:SomeName^7).
it would help if you could give a concrete example of some sample docs, a
sample query, and what results you would expect ... the sample input and
sample output of the system you are int
: Sure, sorry I did not do it before, I just wanted to take minimum of your
: valuable time. So in my custom Similarity class I am trying to implement such
: a logic, where score calculation is only based on field weight and a field
: match - that's it. In other words, if a field matches the query
Thank you for your answer, Chris. I will reply with inline comments as
well. Please see below.
: I need to uniquely identify a document inside of a Similarity class during
: scoring. Is it possible to get value of unique key of a document at this
: point?
Can you tell us a bit more about your
: I need to uniquely identify a document inside of a Similarity class during
: scoring. Is it possible to get value of unique key of a document at this
: point?
Can you tell us a bit more about your usecase ... your problem description
is a bit vague, and sounds like it may be an "XY Problem"...
