Information Retrieval

, Volume 13, Issue 2, pp 157–187 | Cite as

Utilizing passage-based language models for ad hoc document retrieval

Article

Abstract

To cope with the fact that, in the ad hoc retrieval setting, documents relevant to a query could contain very few (short) parts (passages) with query-related information, researchers proposed passage-based document ranking approaches. We show that several of these retrieval methods can be understood, and new ones can be derived, using the same probabilistic model. We use language-model estimates to instantiate specific retrieval algorithms, and in doing so present a novel passage language model that integrates information from the containing document to an extent controlled by the estimated document homogeneity. Several document-homogeneity measures that we present 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; these relevance models also outperform a document-based relevance model. Finally, we demonstrate the merits in using the document-homogeneity measures for integrating document-query and passage-query similarity information for document retrieval.

Keywords

Ad hoc document retrieval Passage-based language models Document homogeneity Relevance models Passage-based relevance models 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Computer Science, Center for Intelligent Information RetrievalUniversity of Massachusetts AmherstAmherstUSA
  2. 2.Faculty of Industrial Engineering and ManagementTechnion—Israel Institute of TechnologyHaifaIsrael

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