On Thu, Feb 16, 2012 at 8:34 AM, Carlos Gonzalez-Cadenas <c...@experienceon.com> wrote: > Hello all: > > We'd like to score the matching documents using a combination of SOLR's IR > score with another application-specific score that we store within the > documents themselves (i.e. a float field containing the app-specific > score). In particular, we'd like to calculate the final score doing some > operations with both numbers (i.e product, sqrt, ...) ... > > 1) Apart from the two options I mentioned, is there any other (simple) way > to achieve this that we're not aware of? >
In general there is always a third option, that may or may not fit, depending really upon how you are trying to model relevance and how you want to integrate with scoring, and thats to tie in your factors directly into Similarity (lucene's term weighting api). For example, some people use index-time boosting, but in lucene index-time boost really just means 'make the document appear shorter'. You might for example, have other boosts that modify term-frequency before normalization, or however you want to do it. Similarity is pluggable into Solr via schema.xml. Since you are using trunk, this is a lot more flexible than previous releases, e.g. you can access things from FieldCache, DocValues, or even your own rapidly-changing float[] or whatever you want :) There are also a lot more predefined models than just the vector space model to work with if you find you can easily imagine your notion of relevance in terms of an existing model. -- lucidimagination.com
