Positional relevance model for pseudo-relevance feedback

Yuanhua Lv, Cheng Xiang Zhai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Pseudo-relevance feedback is an effective technique for improving retrieval results. Traditional feedback algorithms use a whole feedback document as a unit to extract words for query expansion, which is not optimal as a document may cover several different topics and thus contain much irrelevant information. In this paper, we study how to effectively select from feedback documents those words that are focused on the query topic based on positions of terms in feedback documents. We propose a positional relevance model (PRM) to address this problem in a unified probabilistic way. The proposed PRM is an extension of the relevance model to exploit term positions and proximity so as to assign more weights to words closer to query words based on the intuition that words closer to query words are more likely to be related to the query topic. We develop two methods to estimate PRM based on different sampling processes. Experiment results on two large retrieval datasets show that the proposed PRM is effective and robust for pseudo-relevance feedback, significantly outperforming the relevance model in both document-based feedback and passage-based feedback.

Original languageEnglish (US)
Title of host publicationSIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages579-586
Number of pages8
DOIs
StatePublished - 2010
Event33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010 - Geneva, Switzerland
Duration: Jul 19 2010Jul 23 2010

Publication series

NameSIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

Other

Other33rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010
CountrySwitzerland
CityGeneva
Period7/19/107/23/10

Keywords

  • Passage-based feedback
  • Positional language model
  • Positional relevance model
  • Proximity
  • Pseudo-relevance feedback
  • Query expansion

ASJC Scopus subject areas

  • Information Systems

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