Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

ARGUMENTATIONBASED INDEXING FOR INFORMATION RETRIEVAL FROM LEARNED ARTICLES

ARGUMENTATIONBASED INDEXING FOR INFORMATION RETRIEVAL FROM LEARNED ARTICLES Current indexing methods used in automated bibliographic and full text information retrieval assume that knowledge can be adequately represented as a semantic network which is manipulable by means of Boolean operators. However, this semantic approach requires the user to state formally what it is that he wants to find. This paper presents an alternative argumentationbased method. It involves representing a learned article by means of rhetorical structure rather than by a semantic representation of content. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Documentation Emerald Publishing

ARGUMENTATIONBASED INDEXING FOR INFORMATION RETRIEVAL FROM LEARNED ARTICLES

SILLINCE, J.A.A.
Journal of Documentation , Volume 48 (4): 19 – Apr 1, 1992
Download PDF
19 pages

Loading next page...
 
/lp/emerald-publishing/argumentationbased-indexing-for-information-retrieval-from-learned-b7l0V32Pyc
Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0022-0418
DOI
10.1108/eb026905
Publisher site
See Article on Publisher Site

Abstract

Current indexing methods used in automated bibliographic and full text information retrieval assume that knowledge can be adequately represented as a semantic network which is manipulable by means of Boolean operators. However, this semantic approach requires the user to state formally what it is that he wants to find. This paper presents an alternative argumentationbased method. It involves representing a learned article by means of rhetorical structure rather than by a semantic representation of content.

Journal

Journal of Documentation – Emerald Publishing

Published: Apr 1, 1992

There are no references for this article.