Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Technical Papers
A Rule Learning Mechanism for Integration of Concept Hierarchies
Ryutaro ICHISEMasahiro HAMASAKIHideaki TAKEDA
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2004 Volume 19 Issue 6 Pages 521-529

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Abstract
With the rapid advance of information technology, we are able to easily and quickly obtain a great deal of information on almost any topic. One method by which to managing such large amounts of information is to utilize catalogs which organize information within concept hierarchies. However, the concept hierarchy for each catalog is different because one concept hierarchy is not sufficient for all purposes. In the present paper, we address the problem of integrating multiple catalogs for ease of use. The primary problem lies in finding a suitable category in a catalog for each information instance in another catalog. Three approaches can be used to solve this problem: ontology integration approach, instance classification approach and category alignment approach based on categorization similarity. The main idea of this paper is a multiple strategy approach to combine the instance classification approach and the category alignment approach. In order to evaluate the proposed method, we conducted experiments using two actual Internet directories, Yahoo! and Google. The obtained results show that the proposed method improves upon or is competitive with the integration method based only on category alignment or instance classification. Therefore, the proposed catalog integration method is shown to be an effective combination of the instance classification approach and the category alignment approach.
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© 2004 JSAI (The Japanese Society for Artificial Intelligence)
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