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Multinomial Approach and Multiple-Bernoulli Approach for Information Retrieval Based on Language Modeling

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

We present a new retrieval method based on multiple-Bernoulli model and multinomial model in this paper. We use the multiple-Bernoulli model and multinomial model to estimate the term probabilities by importing the conjugate prior and the term frequencies, and use Dirchlet method to smooth the models for solving the ”zero probability” problem of the language model.

Supported by the science research foundation program of Henan University of Science and Technology, China (2004ZY041) and the natural science foundation program of the Henan Educational Department, China (200410464004).

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Author information

Authors and Affiliations

  1. Department of Computer Science, Xi’an Jiaotong University, P.R. China

    Hua Huo & Boqin Feng

  2. School of Electronics and Information, Henan University of Science and Technology, P.R.China

    Hua Huo & Junqiang Liu

Authors
  1. Hua Huo
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  2. Junqiang Liu
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  3. Boqin Feng
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Editor information

Editors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  2. Honda Research Institute Europe GmbH, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Huo, H., Liu, J., Feng, B. (2005). Multinomial Approach and Multiple-Bernoulli Approach for Information Retrieval Based on Language Modeling. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_72

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  • DOI: https://doi.org/10.1007/11539506_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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