Abstract
Nowadays, mobile phones are used not only for calling other people but also used for their various features such as camera, music player, Internet connection etc. Today’s mobile service providers operate in a very competitive environment and they should provide other services to their customers than just call or SMS. One of such services may be to recommend items to their customers that match each customer’s preferences and needs at the time the customer requests a recommendation. In this work, we designed a framework for an easy implementation of a recommendation system for mobile service providers. Using this framework, we implemented as a case study a recommendation model that recommends restaurants to the users based on the content filtering, collaborative filtering and social network of users. We evaluated the performance of our model on real data obtained from a Turkish mobile service company.
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Ozcan, A., Oguducu, S.G. (2010). A Recommendation Framework for Mobile Phones Based on Social Network Data. In: Lee, R., Ma, J., Bacon, L., Du, W., Petridis, M. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2010. Studies in Computational Intelligence, vol 295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13265-0_11
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DOI: https://doi.org/10.1007/978-3-642-13265-0_11
Publisher Name: Springer, Berlin, Heidelberg
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