Understanding conversational utterances often requires
that are very different from those used in understanding well formed
text. Conversations usually consist of short utterances that are often
incomplete and grammatically incorrect. Understanding these utterances
depends heavily on knowing the context of the conversation. For these
reasons, pragmatics, or world knowledge is extremely important. In
practice, when a large amount of pragmatic knowledge is available,
syntactic and semantic analysis become less important. The approach
taken in most current, as well as past, implementations of
conversational agents, is to avoid detailed linguistic analysis of
utterances and instead use relatively simple pattern matching, based on
domain knowledge. However, many domain-specific patterns must be
written to provide credible interactions with the user. Since domain
knowledge is essential for a conversational agent, the approach taken
here is to use pattern matching as the simplest and most direct
This work is related to another project on intelligent environments.
Sammut, C. (2001). Managing Context in a Conversational Agent. Linkoping Electronic Articles in Computer and Information Science. 6(27).
Mak, P., Kang, B.-H., Sammut, C. and Kadous, M. W. (2004). Knowledge Acquisition Module for Conversational Agents. In C. Zhang, H. W. Guesgen and Wai K.Yeap (Eds.), PRICAI 2004: Trends in Artificial Intelligence (Vol. 3157): Springer.
Mohammed Waleed Kadous and Sammut, C. (2004). InCA: A Mobile Conversational Agent. In C. Zhang, H. W. Guesgen and W. K. Yeap (Eds.), 8th Pacific Rim International Conference on Artificial Intelligence (pp. 644 - 653). Auckland, New Zealand: Springer.