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.
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Naganuma, T. et al. (2006). Task-Oriented Mobile Service Recommendation Enhanced by a Situational Reasoning Engine. In: Mizoguchi, R., Shi, Z., Giunchiglia, F. (eds) The Semantic Web – ASWC 2006. ASWC 2006. Lecture Notes in Computer Science, vol 4185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11836025_75
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DOI: https://doi.org/10.1007/11836025_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38329-1
Online ISBN: 978-3-540-38331-4
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