Optimization of Relevance Feedback Weights.

Chris Buckley, Gerard Salton: Optimization of Relevance Feedback Weights. SIGIR 1995: 351-357

@inproceedings{DBLP:conf/sigir/BuckleyS95,
  author    = {Chris Buckley and
               Gerard Salton},
  editor    = {Edward A. Fox and
               Peter Ingwersen and
               Raya Fidel},
  title     = {Optimization of Relevance Feedback Weights},
  booktitle = {SIGIR'95, Proceedings of the 18th Annual International ACM SIGIR
               Conference on Research and Development in Information Retrieval.
                Seattle, Washington, USA, July 9-13, 1995 (Special Issue of
               the SIGIR Forum)},
  publisher = {ACM Press},
  year      = {1995},
  isbn      = {0-89791-714-6},
  pages     = {351-357},
  ee        = {db/conf/sigir/BuckleyS95.html},
  crossref  = {DBLP:conf/sigir/95},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

Methods for learning weight of terms using relevance information from a learning set of documents have been studied for decades in information retrieval research. The approach used here, Dynamic Feedback Optimization, starts with a good weighting scheme based upon Rocchio feedback, and then improves those weights in a dynamic fashion by testing possible changes of query weights on the learning set documents. The resulting optimized query performs 10-15% better thant the original when evaluated on the test set. We discuss the constant tension between describing what a relevant document should contain, and describing what the known relevant documents do contain.

Copyright © 1995 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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Printed Edition

Edward A. Fox, Peter Ingwersen, Raya Fidel (Eds.): SIGIR'95, Proceedings of the 18th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Seattle, Washington, USA, July 9-13, 1995 (Special Issue of the SIGIR Forum). ACM Press 1995, ISBN 0-89791-714-6
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