Hi Dennis, You should check out payloads (arbitrary per-index-term byte[] arrays), which can be used to encode values which are then incorporated into documents' scores, by overriding Similarity.scorePayload():
<http://lucene.apache.org/java/3_0_0/api/core/org/apache/lucene/search/Similarity.html#scorePayload%28int,%20java.lang.String,%20int,%20int,%20byte[],%20int,%20int%29> The Lucene in Action 2 MEAP has a nice introduction to using payloads to influence scoring, in section 6.5. See also this (slightly out-of-date*) blog post "Getting Started with Payloads" by Grant Ingersoll at Lucid Imagination: <http://www.lucidimagination.com/blog/2009/08/05/getting-started-with-payloads/> *Note that since this blog post was written, BoostingTermQuery was renamed to PayloadTermQuery (in Lucene 2.9.0+ ; see http://issues.apache.org/jira/browse/LUCENE-1827 ; wow - this issue isn't mentioned in CHANGES.txt???): <http://lucene.apache.org/java/3_0_0/api/core/org/apache/lucene/search/payloads/PayloadTermQuery.html> Steve On 01/28/2010 at 6:01 AM, Dennis Hendriksen wrote: > I'm struggling to create a performant query in Lucene 3.0.0 in which I > want to combine 'regular' scoring with scores derived from external > sources. > > For each document a fixed set of scores is calculated in the range [0.0, > 1.0>. These scores represent the confidences that a document falls into > categories. So for example document #1 has a score of 0.3 for cat=boys, > 0.2 for cat=girls, 0.1 for cat=toys, 0.05 for cat=animals. > > The 'regular' scoring is calculated using a BooleanQuery with TermQuerys > similar to: -type:H +(title:dna body:dna^1.5) > > In the current naive approach I'm combining the scores as following: - > for each document store the three best categories in the following > fields: > name=cat1st value=boys fieldboost=0.3 > name=cat2nd value=girls fieldboost=0.2 > name=cat3rd value=toys fieldboost=0.1 > Search-time use the following query if you're interested in 'girls': > -type:H +(title:dna body:dna^1.5) cat1st:girls cat2nd:girls cat3rd:girls > or if you're interested in 'boys': > -type:H +(title:dna body:dna^1.5) cat1st:boys cat2nd:boys cat3rd:boys > > Disadvantages of the current approach: > - loss of precision encoding/decoding boosts (performance is important, > so this might be acceptable) > - using TermQuery for the cat fields doesn't make a lot of sense since > the external scores are multiplied by the idf of 'boys'/'girls' and > the querynorm > - the resulting score from the cat field is added to the other query > score instead of multiplied > > Just to give you an idea: the index I'm using is growing in time and > contains about 50 million documents > > Do you have an idea how I can improve my query and still keep high > performance? Or should I combine the scores in the Collector (but this > doesn't seem the right place to retrieve the category scores from the > index)? Is it possible to use a different float->byte encoder per field > to reduce the lack of precision? > > Thanks for your time, > Dennis
