Formal multiple-bernoulli models for language modeling

Proceedings of Sheffield SIGIR - Twenty-Seventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2004, Pages 540-541

  Metzler, Donald ^a   Lavrenko, Victor ^a   Croft, W Bruce ^a  

^a Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

Author keywords

Information retrieval; Language modeling

Indexed keywords

FUNCTIONS; HEURISTIC METHODS; KNOWLEDGE REPRESENTATION; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD ESTIMATION; POLYNOMIALS; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS;

BAYESIAN APPROACH; DIRICHLET SMOOTHING; LANGUAGE MODELING; MAXIMUM A PRIORI (MAP); MULTINOMIAL ASSUMPTION;

INFORMATION RETRIEVAL;

EID: 8644273432     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1008992.1009110     Document Type: Conference Paper

References (4)

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3. H. Zaragoza, D. Hiemstra, M. Tipping, and S. Robertson. Bayesian extension to the language model for ad hoc information retrieval. In Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pages 4-9. ACM Press, 2003.
4. C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval. In Research and Development in Information Retrieval, pages 334-342, 2001.