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Knowledge Acquisition Module for Conversation Agent


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Mak, P, Kang, BH, Sammut, C and Kadous, W 2004 , 'Knowledge Acquisition Module for Conversation Agent', paper presented at the Pacific Knowledge Acquisition Workshop 2004, 09/08/2004 - 10/08/2004, Auckland, New Zealand.

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The focus of traditional conversational agents is placed on natural language processing and understanding the needs of the user. These agents are typically implemented for specific domains such that domain knowledge and conversations are built manually. Domain knowledge of these agents are encoded as conversational content which causes problems is magnified by the lack of knowledge acquisition tools and, as a result, agents find it difficult to adapt to different domains and to update existing knowledge bases.
The framework proposed in this paper aims to rectify this problem by building a module to handle knowledge acquisition. The module acquires knowledge through a case-based methodology called Ripple Down Rules (RDR); a technique that has been employed successfully across a host of expert systems

Item Type: Conference or Workshop Item (Paper)
Authors/Creators:Mak, P and Kang, BH and Sammut, C and Kadous, W
Keywords: Conversation Agent, Multiple Classification Ripple Down Rules, MCRDR, Knowledge Acquisition, Learning
Publisher: School of Computing, Unviersity of Tasmania
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