Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Divergence-from-Randomness Models

  • Giambattista AmatiEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_924


Deviation from randomness


Divergence-from-randomness (DFR) information retrieval models are term-document matching functions that are obtained by the product of two divergence functions. An example of DFR function is that related to Jensen’s information of two probability distributions [ 9, pp. 26–28]:
$$ \sum_i{I}_1\left({\hat{p}}_i^{+}||{\hat{p}}_i\right).{I}_2\left({\hat{p}}_i^{+}||{\hat{p}}_i\right) $$
This is a preview of subscription content, log in to check access.

Recommended Reading

  1. 1.
    Amati G. Frequentist and Bayesian approach to information retrieval. In: Proceedings of the 28th European Conference on IR Research; 2005. p. 13–24.Google Scholar
  2. 2.
    Amati G, Carpineto C, Romano G. Query difficulty, robustness, and selective application of query expansion. In: Proceedings of the 26th European Conference on IR Research; 2004. p. 127–37.Google Scholar
  3. 3.
    Amati G, Van Rijsbergen CJ. Probabilistic models of information retrieval based on measuring the divergence from randomness. ACM Trans Inf Syst. 2002;20(4):357–89.CrossRefGoogle Scholar
  4. 4.
    Gärdenfors P. Knowledge in flux. MIT; 1988.Google Scholar
  5. 5.
    Gaussier E, Clinchant S. The BNB distribution for text modeling. In: ECIR, lecture notes in computer science. Springer; 2008.Google Scholar
  6. 6.
    Good IJ. A casual calculus I. Br J Phil Sci. 1961;11(44):305–18.CrossRefGoogle Scholar
  7. 7.
    Harter SP. A probabilistic approach to automatic keyword indexing. PhD thesis, Thesis No. T25146. Graduate Library, The University of Chicago; 1974.Google Scholar
  8. 8.
    He I, Ounis B. On setting the hyper-parameters of the term frequency normalisation for information retrieval. ACM Trans Inf Syst. 2007;25(3).Google Scholar
  9. 9.
    Kullback S. Information theory and statistics. New York: Wiley; 1959.zbMATHGoogle Scholar
  10. 10.
    Ounis I, Amati G, Plachouras V, He B, Macdonald C, Johnson D. Terrier information retrieval platform. In: Proceedings of the 27th European Conference on IR Research; 2005. p. 517–9.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Fondazione Ugo BordoniRomeItaly

Section editors and affiliations

  • Giambattista Amati
    • 1
  1. 1.Fondazione Ugo BordoniRomeItaly