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A nonparametric term weighting method for information retrieval based on measuring the divergence from independence

Date

2014

Author

Kocabas, Ilker
Dincer, Bekir Taner
Karaoglan, Bahar
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Abstract

In this article, we introduce an out-of-the-box automatic term weighting method for information retrieval. The method is based on measuring the degree of divergence from independence of terms from documents in terms of their frequency of occurrence. Divergence from independence has a well-establish underling statistical theory. It provides a plain, mathematically tractable, and nonparametric way of term weighting, and even more it requires no term frequency normalization. Besides its sound theoretical background, the results of the experiments performed on TREC test collections show that its performance is comparable to that of the state-of-the-art term weighting methods in general. It is a simple but powerful baseline alternative to the state-of-the-art methods with its theoretical and practical aspects.

Source

Information Retrieval

Volume

17

Issue

2

URI

https://doi.org/10.1007/s10791-013-9225-4
https://hdl.handle.net/20.500.12809/3490

Collections

  • Scopus İndeksli Yayınlar Koleksiyonu [6219]
  • WoS İndeksli Yayınlar Koleksiyonu [6466]



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