Knowledge Representation, Connectionism, and Conceptual Retrieval.
Ronald J. Brachman, Deborah L. McGuinness:
Knowledge Representation, Connectionism, and Conceptual Retrieval.
SIGIR 1988: 161-174@inproceedings{DBLP:conf/sigir/BrachmanM88,
author = {Ronald J. Brachman and
Deborah L. McGuinness},
editor = {Yves Chiaramella},
title = {Knowledge Representation, Connectionism, and Conceptual Retrieval},
booktitle = {SIGIR'88, Proceedings of the 11th Annual International ACM SIGIR
Conference on Research and Development in Information Retrieval,
Grenoble, France, June 13-15, 1988},
publisher = {ACM},
year = {1988},
pages = {161-174},
ee = {db/conf/sigir/BrachmanM88.html},
crossref = {DBLP:conf/sigir/88},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
Knowledge Representation (KR) systems provide support for Artificial Intelligence systems that
reason about relationships between objects in their domains of expertise. Because of their support
for inference, KR systems appear to have potential to enrich the kind of retrievals that IR systems
might make. Ironically, however, the most useful KR systems are limited to reasoning based on a
rigid notion of validity, and thus are awkward to use when relevant but inexact retrievals are desired.
We have been exploring the potential of a "connectionist" model--the Boltzmann Machine--to
overcome this limitation. We report on a number of experiments in which we use a connectionist
simulator to support similarity-based reasoning in a frame representation. We draw some tentative,
mixed conclusions on the potential for a union of KR, IR, and connectionism.
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BibTeX
Printed Edition
Yves Chiaramella (Ed.):
SIGIR'88, Proceedings of the 11th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Grenoble, France, June 13-15, 1988.
ACM 1988
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