Abstract
The recent spread of the so called Web of Data has made available a vast amount of interconnected data, paving the way to a new generation of ubiquitous applications able to exploit the information encoded in it. In this paper we present Cinemappy, a location-based application that computes contextual movie recommendations. Cinemappy refines the recommendation results of a content-based recommender system by exploiting contextual information related to the current spatial and temporal position of the user. The content-based engine leverages graph information within DBpedia, one of the best-known datasets publicly available in the Linked Open Data (LOD) project.
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Ostuni, V.C., Gentile, G., Di Noia, T., Mirizzi, R., Romito, D., Di Sciascio, E. (2013). Mobile Movie Recommendations with Linked Data. In: Cuzzocrea, A., Kittl, C., Simos, D.E., Weippl, E., Xu, L. (eds) Availability, Reliability, and Security in Information Systems and HCI. CD-ARES 2013. Lecture Notes in Computer Science, vol 8127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40511-2_29
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DOI: https://doi.org/10.1007/978-3-642-40511-2_29
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