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A rough set model with ontologies for discovering maximal association rules in document collections

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Bi, Y, Anderson, TJ and McClean, SI (2003) A rough set model with ontologies for discovering maximal association rules in document collections. Knowl.-Based Syst., 16 (5-6). pp. 243-251. [Journal article]

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URL: http://dx.doi.org/10.1016/S0950-7051(03)00025-X

Abstract

In this paper we investigate the applicability of a Rough Set model and method to discover maximal associations from a collection of text documents, and compare its applicability with that of the maximal association method. Both methods are based on computing co-occurrences of various sets of keywords, but it has been shown that by using the Rough Set method, rules discovered are similar to maximal association rules, and it is much simpler than the maximal association method. In addition, we also present an alternative strategy to taxonomies required in the above methods, instead of building taxonomies based on labelled document collections themselves. This is to effectively utilise ontologies which will increasingly be deployed on the Internet.

Item Type:Journal article
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
Computer Science Research Institute > Information and Communication Engineering
ID Code:7568
Deposited By:Professor Sally McClean
Deposited On:20 Jan 2010 15:51
Last Modified:20 Jan 2010 15:51

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