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Divergence-from-Randomness Models

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Encyclopedia of Database Systems

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Recommended Reading

  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. 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. 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.

    Article  Google Scholar 

  4. Gärdenfors P. Knowledge in flux. MIT; 1988.

    Google Scholar 

  5. Gaussier E, Clinchant S. The BNB distribution for text modeling. In: ECIR, lecture notes in computer science. Springer; 2008.

    Google Scholar 

  6. Good IJ. A casual calculus I. Br J Phil Sci. 1961;11(44):305–18.

    Article  Google Scholar 

  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. 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. Kullback S. Information theory and statistics. New York: Wiley; 1959.

    MATH  Google Scholar 

  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 

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Author information

Authors and Affiliations

  1. Fondazione Ugo Bordoni, Rome, Italy

    Giambattista Amati

Authors
  1. Giambattista Amati
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Corresponding author

Correspondence to Giambattista Amati .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

Section Editor information

  1. Fondazione Ugo Bordoni, Rome, Italy

    Giambattista Amati

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Amati, G. (2018). Divergence-from-Randomness Models. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_924

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