Relevance Feedback Revisited.

Donna Harman: Relevance Feedback Revisited. SIGIR 1992: 1-10

@inproceedings{DBLP:conf/sigir/Harman92,
  author    = {Donna Harman},
  editor    = {Nicholas J. Belkin and
               Peter Ingwersen and
               Annelise Mark Pejtersen},
  title     = {Relevance Feedback Revisited},
  booktitle = {Proceedings of the 15th Annual International ACM SIGIR Conference
               on Research and Development in Information Retrieval. Copenhagen,
               Denmark, June 21-24, 1992},
  publisher = {ACM},
  year      = {1992},
  isbn      = {0-89791-523-2},
  pages     = {1-10},
  ee        = {db/conf/sigir/Harman92.html},
  crossref  = {DBLP:conf/sigir/92},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

Researchers have found relevance feedback to be effective in interactive information retrieval, although few formal user experiments have been made. In order to run a user experiment on a large document collection, experiments were performed at NIST to complete some of the missing links found in using the probabilistic retrieval model. These experiments, using the Cranfield 1400 collection, showed the importance of query expansion in addition to query reweighting, and showed that adding as few as 20 well-selected terms could result in performance improvements of over 100%. Additionally it was shown that performing multiple iterations of feedback is highly effective.

Copyright © 1992 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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BibTeX

Printed Edition

Nicholas J. Belkin, Peter Ingwersen, Annelise Mark Pejtersen (Eds.): Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Copenhagen, Denmark, June 21-24, 1992. ACM 1992, ISBN 0-89791-523-2
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Referenced by

Markus Tresch, Allen Luniewski: An Extensible Classifier for Semi-Structured Documents. CIKM 1995: 226-233

BibTeX

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