Knowledge-intensive conceptual retrieval and passage extraction of biomedical literature

Wei Zhou, Clement Yu, Neil Smalheiser, Vetle Torvik, Jie Hong

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

Abstract

This paper presents a study of incorporating domain-specific knowledge (i.e., information about concepts and relationships between concepts in a certain domain) in an information retrieval (IR) system to improve its effectiveness in retrieving biomedical literature. The effects of different types of domain-specific knowledge in performance contribution are examined. Based on the TREC platform, we show that appropriate use of domain-specific knowledge in a proposed conceptual retrieval model yields about 23% improvement over the best reported result in passage retrieval in the Genomics Track of TREC 2006.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07
Pages655-662
Number of pages8
DOIs
StatePublished - Nov 30 2007
Externally publishedYes
Event30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 - Amsterdam, Netherlands
Duration: Jul 23 2007Jul 27 2007

Publication series

NameProceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07

Other

Other30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07
CountryNetherlands
CityAmsterdam
Period7/23/077/27/07

Keywords

  • Biomedical documents
  • Document retrieval
  • Passage extraction

ASJC Scopus subject areas

  • Information Systems
  • Software
  • Applied Mathematics

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  • Cite this

    Zhou, W., Yu, C., Smalheiser, N., Torvik, V., & Hong, J. (2007). Knowledge-intensive conceptual retrieval and passage extraction of biomedical literature. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 (pp. 655-662). (Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07). https://doi.org/10.1145/1277741.1277853