Knowledge Acquisition Module for Conversation Agent
Mak, P and Kang, BH and Sammut, C and Kadous, W (2004) Knowledge Acquisition Module for Conversation Agent. In: 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)|
|Keywords:||Conversation Agent, Multiple Classification Ripple Down Rules, MCRDR, Knowledge Acquisition, Learning|
|Deposited By:||utas eprints|
|Deposited On:||05 Oct 2004|
|Last Modified:||18 Jul 2008 19:37|
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