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Issue No. 05 - September/October (2007 vol. 22)
ISSN: 1541-1672
pp: 23-32
Dario Bottazzi , University of Bologna
Rebecca Montanari , University of Bologna
Alessandra Toninelli , University of Bologna
Recent advances in wireless technologies and mobile devices let users form opportunistic social networks of interests with nearby users. However, anytime, anywhere social networks raise several technological issues, including the detection of user location; the modeling, acquisition, and analysis of a user's characterizing properties; and the dynamic extraction of social networks. SAMOA, a semantic context-aware middleware approach, lets you create anytime, anywhere social networks among users in physical proximity. SAMOA separates social-network management from application logic by providing reusable middleware support for various social application scenarios. In addition, SAMOA exploits semantic-based context modeling and matching algorithms for social-network extraction. This article is part of a special issue on social computing.
social networking, middleware, context modeling, matching algorithms

R. Montanari, A. Toninelli and D. Bottazzi, "Context-Aware Middleware for Anytime, Anywhere Social Networks," in IEEE Intelligent Systems, vol. 22, no. , pp. 23-32, 2007.
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