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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Utilizing Passage-Based Language Models for Document Retrieval
verfasst von : Michael Bendersky, Oren Kurland
Erschienen in: Advances in Information Retrieval
Verlag: Springer Berlin Heidelberg
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We show that several previously proposed
passage-based
document ranking principles, along with some new ones, can be derived from the same probabilistic model. We use language models to instantiate specific algorithms, and propose a
passage language model
that integrates information from the ambient document to an extent controlled by the estimated
document homogeneity
. Several document-homogeneity measures that we propose yield passage language models that are more effective than the standard passage model for basic document retrieval and for constructing and utilizing
passage-based relevance models
; the latter outperform a document-based relevance model. We also show that the homogeneity measures are effective means for integrating document-query and passage-query similarity information for document retrieval.