Improving sentence retrieval with an importance prior

Leif Azzopardi, Ronald T. Fernández, David E. Losada

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

Abstract

The retrieval of sentences is a core task within Information Retrieval. In this poster we employ a Language Model that incorporates a prior which encodes the importance of sentences within the retrieval model. Then, in a set of comprehensive experiments using the TREC Novelty Tracks, we show that including this prior substantially improves retrieval effectiveness, and significantly outperforms the current state of the art in sentence retrieval.
Original languageEnglish
Title of host publicationSIGIR '10 Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of PublicationNew York, NY, USA
Pages779-780
Number of pages2
DOIs
Publication statusPublished - 19 Jul 2010
Externally publishedYes

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Keywords

  • language model
  • sentence retrieval

Cite this

Azzopardi, L., Fernández, R. T., & Losada, D. E. (2010). Improving sentence retrieval with an importance prior. In SIGIR '10 Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 779-780). New York, NY, USA. https://doi.org/10.1145/1835449.1835612