Hybrid soft categorisation in conceptual spaces

Lee, Ickjai (2004) Hybrid soft categorisation in conceptual spaces. In: Proceedings of Fourth International Conference on Hybrid Intelligent Systems, pp. 74-79. From: Fourth International Conference on Hybrid Intelligent Systems, 5 - 8 December 2004, Kitakyushu, Japan.

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Abstract

Understanding the process of categorization is of great importance for building intelligent agents. Formulated categories help agents find information easier and understand the external world better. Instance-based categorization and prototype-based categorization have been two dominant approaches in the AI community. However, they share some drawbacks in common. First, they are crisp boundary based hard categorizations (similar to classification). Second, they are not well-suited for dynamic category learning and formation. In this paper, we propose a hybrid soft categorization in the conceptual level that overcomes these drawbacks. The hybrid soft categorization merges the two popular hard categorizations and provides a robust fuzzy boundary-based soft categorization.

Item ID: 7633
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: categorisation
ISBN: 978-0-7695-2291-3
Date Deposited: 28 Jul 2010 00:34
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
Citation Count from Scopus Scopus 0
Downloads: Total: 2
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