Abstract
Exploring new applications and services for mobile environments has generated considerable excitement among both industries and academics. In this paper we propose a context-aware recommender system that accommodates user’s needs with location-dependent multimedia information available in a mobile environment related to an indoor scenario. Specifically, we propose a recommender system for the planning of browsing activities that are based on objects features, users’ behaviours and on the current context the state of which is captured by apposite sensor networks. We present the features of such a system and we discuss the proposed approach.
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Amato, F., Mazzeo, A., Moscato, V., Picariello, A. (2013). A Recommendation System for Browsing of Multimedia Collections in the Internet of Things. In: Bessis, N., Xhafa, F., Varvarigou, D., Hill, R., Li, M. (eds) Internet of Things and Inter-cooperative Computational Technologies for Collective Intelligence. Studies in Computational Intelligence, vol 460. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34952-2_16
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DOI: https://doi.org/10.1007/978-3-642-34952-2_16
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