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Book Sections Year : 2003

Conversation Mining in Multi-agent Systems

Abstract

The complexity of Multi-Agent Systems is constantly increasing. With the growth of the number of agents, interactions between them draw complexan d huge conversations, i.e. sequences of messages exchanged inside the system. In this paper, we present a knowledge discovery process, mining those conversations to infer their underlying models, using stochastic grammatical inference techniques. We present some experiments that show the process we design is a good candidate to observe the interactions between the agents and infer the conversation models they build together.

Dates and versions

emse-00745169 , version 1 (24-10-2012)

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Cite

Arnaud Mounier, Olivier Boissier, François Jacquenet. Conversation Mining in Multi-agent Systems. Marík, Vladimír; Pechoucek, Michal; Müller, Jörg. Multi-Agent Systems and Applications III, Springer Berlin / Heidelberg, pp 1068 - 1068, 2003, Lecture Notes in Computer Science, 978-3-540-40450-7. ⟨10.1007/3-540-45023-8_16⟩. ⟨emse-00745169⟩
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