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@inproceedings{DBLP:conf/sigir/FungCAT90,
author = {Robert M. Fung and
Stuart L. Crawford and
Lee A. Appelbaum and
Richard M. Tong},
editor = {Jean-Luc Vidick},
title = {An Architecture for Probabilistic Concept-Based Information Retrieval},
booktitle = {SIGIR'90, 13th International Conference on Research and Development
in Information Retrieval, Brussels, Belgium, 5-7 September 1990,
Proceedings},
publisher = {ACM},
year = {1990},
isbn = {0-89791-408-2},
pages = {455-467},
ee = {db/conf/sigir/FungCAT90.html},
crossref = {DBLP:conf/sigir/90},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
While concept-based methods for information retrievul can provide improved performance over more conventional techniques, they require large amounts of effort to acquire the concepts and their qualitative and quantitative relationships.
This paper discusses an architecture for probabilistic concept-based information retrieval which addresses the knowledge acquisition problem. The architecture makes use of the probabilistic networks technology for representing and reasoning about concepts and includes a knowledge acquisition component which partia]]y automates the construction of concept knowledge bases from data.
We describe two experiments that apply the architecture to the task of retrieving documents about terrorism from a set of documents from the Reuters news service. The experiments provide positive evidence that the architecture design is feasible and that there are advantages to concept-based methods.
Copyright © 1990 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.