A Belief Network Model for IR.

Berthier A. Ribeiro-Neto, Richard R. Muntz: A Belief Network Model for IR. SIGIR 1996: 253-260

@inproceedings{DBLP:conf/sigir/RibeiroM96,
  author    = {Berthier A. Ribeiro-Neto and
               Richard R. Muntz},
  editor    = {Hans-Peter Frei and
               Donna Harman and
               Peter Sch{\"a}uble and
               Ross Wilkinson},
  title     = {A Belief Network Model for IR},
  booktitle = {Proceedings of the 19th Annual International ACM SIGIR Conference
               on Research and Development in Information Retrieval, SIGIR'96,
               August 18-22, 1996, Zurich, Switzerland (Special Issue of the
               SIGIR Forum)},
  publisher = {ACM},
  year      = {1996},
  isbn      = {0-89791-792-8},
  pages     = {253-260},
  ee        = {db/conf/sigir/RibeiroM96.html},
  crossref  = {DBLP:conf/sigir/96},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

BibTeX

Abstract

We introduce a belief network model for IR which is derived from probabilistic considerations over a clearly defined sample space. This model subsumes the classical models in IR and generalizes the inference network model of Turtle and Croft. Further, we show how to extend the model with information from other queries (which we call contexts) to yield improved retrieval performance.

Copyright © 1996 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

Hans-Peter Frei, Donna Harman, Peter Schäuble, Ross Wilkinson (Eds.): Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'96, August 18-22, 1996, Zurich, Switzerland (Special Issue of the SIGIR Forum). ACM 1996, ISBN 0-89791-792-8
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