A retrospective study of probabilistic context-based retrieval

H. C. Wu, Wing Pong Robert Luk, K. F. Wong, K. L. Kwok, Wenjie Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

We propose a novel probabilistic retrieval model which weights terms according to their contexts in documents. The term weighting function of our model is similar to the language model and the binary independence model. The retrospective experiments (i.e., relevance information is present) illustrate the potential of our probabilistic context-based retrieval where the precision at the top 30 documents is about 43% for TREC-6 data and 52% for TREC-7 data.
Original languageEnglish
Title of host publicationSIGIR 2005 - Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages663-664
Number of pages2
DOIs
Publication statusPublished - 1 Dec 2005
Event28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005 - Salvador, Brazil
Duration: 15 Aug 200519 Aug 2005

Conference

Conference28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2005
CountryBrazil
CitySalvador
Period15/08/0519/08/05

Keywords

  • context
  • retrospective experiment

ASJC Scopus subject areas

  • Information Systems

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