Task-oriented mobile service recommendation enhanced by a situational reasoning engine

Abstract

In this paper, we propose a system that recommends appropriate mobile services from the viewpoint of the user's task which fits with user's situation in the real world. Key components are a situation provider that reason on user situation based on context gathered from multiple sources, and a task knowledge base which stores semantic task descriptions of what actions the mobile user is likely to perform in daily life. We present the architecture of the proposed system; the situational reasoning engine which makes use of context ontologies represented using OWL, and the task knowledge base which stores OWL-S-based descriptions of the user's tasks in the real world. Finally, we describe a prototypical implementation and some realized use cases. © Springer-Verlag Berlin Heidelberg 2006.