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Erschienen in:
2003 | OriginalPaper | Buchkapitel
Probabilistic Relevance Models Based on Document and Query Generation
verfasst von : John Lafferty, ChengXiang Zhai
Erschienen in: Language Modeling for Information Retrieval
Verlag: Springer Netherlands
Enthalten in: Professional Book Archive
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We give a unified account of the probabilistic semantics underlying the language modeling approach and the traditional probabilistic model for information retrieval, showing that the two approaches can be viewed as being equivalent probabilistically, since they are based on different factorizations of the same generative relevance model. We also discuss how the two approaches lead to different retrieval frameworks in practice, since they involve component models that are estimated quite differently.