PhraseQuery Scorer for scoring sub phrase matches
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                 Key: LUCENE-1853
                 URL: https://issues.apache.org/jira/browse/LUCENE-1853
             Project: Lucene - Java
          Issue Type: Improvement
          Components: Search
         Environment: Lucene/Java
            Reporter: Preetam Rao
            Priority: Minor
             Fix For: 2.9


For a query like "homes in new york with swimming pool", if a document's field 
matches only "new york" it should get scored and it should get scored higher 
than two separate matches "new" and "york".  Also, a 3 word sub phrase match 
must gets scored considerably higher than a 2 word sub phrase match. (boost 
factor should be configurable)

If a user query is taken as is without parsing and is searched against multiple 
fields, where each sub-phrase can match against a different field, this kind of 
query is useful. 

Using shingles for this use case, means each field of each document needs to be 
indexed as shingles of all (1..N)-grams as well as the query. (Please correct 
me if I am wrong.)

The scorer could also support 
- ignoring of idf and/or field norms, (so that factors outside the document 
don't influence scoring)
- consider only the longest match (for example match on "new york" is scored 
and considered rather than "new" furniture and "york" city)
- ignore duplicates ("new york" appearing twice or thrice does not make any 
difference)

This kind of query (Phrase Query with SubPhraseScorer) could be combined with 
DisMax query. For example, something like solr's dismax request handler can be 
made to use this query where we run a user query as it is against all fields 
and configure each field with above configurations.

I have also attached a patch with comments and test cases in case, my 
description is not clear enough. Would appreciate alternatives or feedback. The 
goal is to give more control via configuration when searching using user 
entered queries against multiple fields where sub phrases have special 
significance.

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