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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