Dynamic association rules mining to improve intermediation between user multi-channel interactions and interactive e-services

Authors:
Vincent Chevrin;Olivier Couturier
Affiliations:
Laboratoire Trigone, LIFL, CUEEP, Villeneuve d'Ascq Cedex, France;Centre de Recherche en Informatique de Lens-IUT de Lens, Lens Cedex, France
Venue:
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Year:
2007

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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).