Examples of BlendedTermQuery

• org.apache.lucene.queries.BlendedTermQuery
  BlendedTermQuery can be used to unify term statistics across one or more fields in the index. A common problem with structured documents is that a term that is significant in on field might not be significant in other fields like in a scenario where documents represent users with a "first_name" and a "second_name". When someone searches for "simon" it will very likely get "paul simon" first since "simon" is a an uncommon last name ie. has a low document frequency. This query tries to "lie" about the global statistics like document frequency as well total term frequency to rank based on the estimated statistics.

  While aggregating the total term frequency is trivial since it can be summed up not every {@link org.apache.lucene.search.similarities.Similarity}makes use of this statistic. The document frequency which is used in the {@link org.apache.lucene.search.similarities.DefaultSimilarity}can only be estimated as an lower-bound since it is a document based statistic. For the document frequency the maximum frequency across all fields per term is used which is the minimum number of documents the terms occurs in.

Examples of org.apache.lucene.queries.BlendedTermQuery