[jira] [Created] (LUCENE-6818) Implementing Divergence from Independence (DFI) Term-Weighting for Lucene/Solr

["Ahmet Arslan (JIRA)" <ji...@apache.org>]

Ahmet Arslan created LUCENE-6818:
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             Summary: Implementing Divergence from Independence (DFI) Term-Weighting for Lucene/Solr
                 Key: LUCENE-6818
                 URL: https://issues.apache.org/jira/browse/LUCENE-6818
             Project: Lucene - Core
          Issue Type: New Feature
          Components: core/query/scoring
    Affects Versions: 5.3
            Reporter: Ahmet Arslan
            Priority: Minor
             Fix For: Trunk


As explained in the [write-up|http://lucidworks.com/blog/flexible-ranking-in-lucene-4], many state-of-the-art ranking model implementations are added to Apache Lucene. 

This issue aims to include DFI model, which is the non-parametric counterpart of the Divergence from Randomness (DFR) framework.

DFI is both parameter-free and non-parametric:

* parameter-free: it does not require any parameter tuning or training.
 * non-parametric: it does not make any assumptions about word frequency distributions on document collections.

It is highly recommended *not* to remove stopwords (very common terms: the, of, and, to, a, in, for, is, on, that, etc) with this similarity.

For more information see: [A nonparametric term weighting method for information retrieval based on measuring the divergence from independence|http://dx.doi.org/10.1007/s10791-013-9225-4]



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