Abstract
This paper deals with multi-channel interaction managing thru an intermediation between channels and Interactive e-Services (IeS). After work on modeling and theoretical framework, we implemented a platform: Ubi-Learn, which is able to manage this kind of interaction thru an intermediation middleware based on a Multi-Agents System (MAS): Jade. The issue addressed here is linked to the way you choose a channel depending on the user’s task. First, we have encoded several ad hoc rules (tacit knowledge) into the system. In this paper, we present our new approach based on association rules mining approach which allows us to propose automatically several dynamic rules (explicit knowledge).
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Chevrin, V., Couturier, O. (2007). Dynamic Association Rules Mining to Improve Intermediation Between User Multi-channel Interactions and Interactive e-Services. In: Jacko, J.A. (eds) Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments. HCI 2007. Lecture Notes in Computer Science, vol 4552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73110-8_28
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DOI: https://doi.org/10.1007/978-3-540-73110-8_28
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