Abstract
In this paper, I present a computational approach to understanding and augmenting the conversational knowledge process that is a collective activity for knowledge creation, management, and application where conversational communications are used as a primary means of interaction among participating agents. The key idea is conversation quantization, a technique of approximating a continuous flow of conversation by a series of conversation quanta that represent points of the discourse. Conversation quantization enables to implement a rather robust conversational system by basing it on a large amount of conversational quanta collected from the real world. I survey major results concerning capturing, accumulating, presenting, and understanding conversation quanta.
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Nishida, T. (2005). Conversation Quantization for Conversational Knowledge Process. In: Bhalla, S. (eds) Databases in Networked Information Systems. DNIS 2005. Lecture Notes in Computer Science, vol 3433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31970-2_2
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DOI: https://doi.org/10.1007/978-3-540-31970-2_2
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