Statistical language models for information retrieval

Statistical language models for information retrieval

by Zhai, ChengXiang

Type Book
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Title Statements

  • Full title :Statistical language models for information retrieval / ChengXiang Zhai.

Edition Statements

  • Publication Date:2009.

Publication Statements

  • Publisher(s):Morgan & Claypool
  • Place of Publication:San Rafael, Calif
  • Language:eng
  • Publication Date:2009.

The Physical Object

  • Description:xiii, 125 s.

Edition Identifiers

  • ISBN:9781598295900, 159829590X
  • oclc:ocn938028143

Table of Contents

Introduction -- Basic concepts in information retrieval -- Statistical language models -- Overview of information retrieval models -- Similarity-based models -- Probabilistic relevance models -- Probabilistic inference models -- Axiomatic retrieval framework -- Decision-theoretic retrieval framework -- Summary -- Simple query likelihood retrieval model -- Basic idea -- Event models for [theta] d -- Multinomial [theta] d -- Multiple Bernoulli [theta] d -- Multiple Poisson [theta] d -- Comparison of the three models -- Estimation of [theta] d -- A general smoothing strategy using collection language model -- Jelinek-Mercer smoothing (fixed coefficient interpolation) -- Dirichlet prior smoothing -- Absolute discounting smoothing -- Interpolation vs. backoff -- Other smoothing methods -- Comparison of different smoothing methods -- Smoothing and TF-IDF weighting -- Two-stage smoothing -- Exploit document prior -- Summary -- Complex query likelihood retrieval model -- Document-specific smoothing of [theta]d -- Cluster-based smoothing -- Document expansion -- Beyond unigram models -- Parsimonious language models -- Full Bayesian query likelihood -- Translation model -- Summary -- Probab…

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