Mean-Field Approach to a Probabilistic Model in Information Retrieval

Bin Wu, K. Y.Michael Wong, David Bodoff

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We study an explicit parametric model of documents, queries, and relevancy assessment for Information Retrieval (IR). Mean-field methods are applied to analyze the model and derive efficient practical algorithms to estimate the parameters in the problem. The hyperparameters are estimated by a fast approximate leave-one-out cross-validation procedure based on the cavity method. The algorithm is further evaluated on several benchmark databases by comparing with standard algorithms in IR.

Original languageEnglish
Title of host publicationNIPS 2002
Subtitle of host publicationProceedings of the 15th International Conference on Neural Information Processing Systems
EditorsSuzanna Becker, Sebastian Thrun, Klaus Obermayer
PublisherMIT Press Journals
Pages497-504
Number of pages8
ISBN (Electronic)0262025507, 9780262025508
StatePublished - 2002
Externally publishedYes
Event15th International Conference on Neural Information Processing Systems, NIPS 2002 - Vancouver, Canada
Duration: 9 Dec 200214 Dec 2002

Publication series

NameNIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Conference

Conference15th International Conference on Neural Information Processing Systems, NIPS 2002
Country/TerritoryCanada
CityVancouver
Period9/12/0214/12/02

Bibliographical note

Publisher Copyright:
© NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems. All rights reserved.

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications
  • Information Systems

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