An Agent-Based Approach to Adapt Multimedia Web Content in Ubiquitous Environment

An Agent-Based Approach to Adapt Multimedia Web Content in Ubiquitous Environment

Domenico Rosaci, Giuseppe M.L. Sarnè
Copyright: © 2012 |Pages: 25
DOI: 10.4018/978-1-61350-107-8.ch003
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Abstract

Nowadays, Ubiquitous Computing allows a high number of multimedia contents to be accessible anywhere and anytime by using several devices, also characterized from limited computational and storage resources. To support users in multimedia choices, different recommender systems have been proposed in the past, but any of them considers the effects of the exploited devices, even though users show different behaviours in presence of different devices. This chaptertries to give a contribution in this setting, proposing a new agent-based recommender system in which each device is provided with a client agent able to monitor the user’s behaviour performed on that device. A unique server agent associated with that user collects from his/her devices this information to build a global profile, periodically returned to the client agents. Finally, recommendations of multimedia resources are generated from the collaboration among a recommender agent, associated with a Web site, and the client agent running on the device currently exploited by the user. Some experiments confirm the high quality of the recommendations generated by the proposed approach.
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Introduction

Nowadays, Ubiquitous Computing (Waiser, 1991) is enveloping everyday life with an increasing number of personalized services accessible to the people anywhere and anytime by several devices. As a consequence, users have to continuously deal with an overwhelming amount of information covering a number of areas and contexts. This trend, supported by the continuous evolution of information and communication technologies, implies a significant modification of users’ habits. In particular, new low power and inexpensive computational devices, user-friendly interfaces and ubiquitous network infrastructures heavily contributed to a wide diffusion of Multimedia Resources (MRs) on the Web. In this scenario, an emerging issue is that of allowing users to simply discovery new MRs. To this aim, acquiring knowledge about users’ characteristics (i.e., their behaviours, interests and preferences) and context information (i.e., location, environmental conditions and device characteristics) it is essential to recommend the most appropriate MRs.

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