Relevance Feedback and Inference Networks.

David Haines, W. Bruce Croft: Relevance Feedback and Inference Networks. SIGIR 1993: 2-11

@inproceedings{DBLP:conf/sigir/HainesC93,
  author    = {David Haines and
               W. Bruce Croft},
  editor    = {Robert Korfhage and
               Edie M. Rasmussen and
               Peter Willett 0002},
  title     = {Relevance Feedback and Inference Networks},
  booktitle = {Proceedings of the 16th Annual International ACM-SIGIR Conference
               on Research and Development in Information Retrieval. Pittsburgh,
               PA, USA, June 27 - July 1, 1993},
  publisher = {ACM},
  year      = {1993},
  isbn      = {0-89791-605-0},
  pages     = {2-11},
  ee        = {db/conf/sigir/HainesC93.html},
  crossref  = {DBLP:conf/sigir/93},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Relevance feedback, which modifies queries using judgements of the relevance of a few, highly-ranked documents, has historically been an important method for increasing the performance of information retrieval systems. In this paper, we extend the inference network model introduced by Turtle and Croft to include relevance feedback techniques. The difference between relevance feedback on text abstracts and full text collections is studied. Preliminary results for relevance feedback on the structured queries supported by the inference net model are also reported.

Copyright © 1993 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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Robert Korfhage, Edie M. Rasmussen, Peter Willett (Eds.): Proceedings of the 16th Annual International ACM-SIGIR Conference on Research and Development in Information Retrieval. Pittsburgh, PA, USA, June 27 - July 1, 1993. ACM 1993, ISBN 0-89791-605-0
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