Preference-Driven Personalization for Flexible Digital Item Adaptation

Abstract

Abstract The delivery of multimedia content often needs the adaptation of the content in order to satisfy user constraints. With the Digital Item Adaptation part, the MPEG-21 standard already defines a useful frame-work to handle this task. However, in modern service-oriented architectures the functionality of adaptation is split over several services. Hence, the central instantiation of a suitable service chain needs to tackle a complex multiobjective optimization problem. In this problem between content choice and possible adaptations the current preference model in the MPEG-7/21 standard still lacks expressiveness. In the course of this paper we demonstrate this shortcoming and how the integration of more powerful models can ease the instantiation problem. Furthermore we explain how to efficiently evaluate preference trade-offs by evaluating skyline queries as currently investigated in the field of information systems. As a running example we use preference-based content adaptation in a typical media streaming application with Web services as basic modules. The contribution of our framework is to enable a central coordinator to instantiate an executable service composition chain by integrating all needed Web services to adapt the multimedia content in the best possible fashion in the sense of Pareto optimality