Soft behaviour modelling of user communities

A soft modelling approach for describing behaviour in on-line user communities is introduced in this work. Behaviour models of individual users in dynamic virtual environments have been described in the literature in terms of timed transition automata; they have various drawbacks. Soft multi/agent behaviour automata are defined and proposed to describe multiple user behaviours and to recognise larger classes of user group histories, such as group histories which contain unexpected behaviours. The notion of deviation from the user community model allows defining a soft parsing process which assesses and evaluates the dynamic behaviour of a group of users interacting in virtual environments, such as e-learning and e-business platforms. The soft automaton model can describe virtually infinite sequences of actions due to multiple users and subject to temporal constraints. Soft measures assess a form of distance of observed behaviours by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed history as well as actions performed by unexpected users. The proposed model allows the soft recognition of user group histories also when the observed actions only partially meet the given behaviour model constraints. This approach is more realistic for real-time user community support systems, concerning standard boolean model recognition, when more than one user model is potentially available, and the extent of deviation from community behaviour models can be used as a guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an e-learning platform and plan compilation of the soft multi-agent behaviour automaton show the expressiveness of the proposed model

Modeling Web Applications reacting to User Behaviors

Many current research efforts address the problem of personalizing the Web experience for each user with respect to user’s identity and/or context. In this paper we propose a new high-level model for the specification of Web applications that takes into account the manner in which users interact with the application for supplying appropriate contents or gathering profile data. We therefore consider entire behaviors (rather than single properties) as the smallest information units, allowing for automatic restructuring of application components. For this purpose, a high-level Event-Condition-Action (ECA) paradigm is proposed, which enables capturing arbitrary (and timed) clicking behaviors. Also, the architecture and components of a first prototype implementation are discussed