Abstract
Recommender systems are found in many modern web sites for applications such as recommending products to customers. In this paper we propose a new method for recommender system that employs the users’ social network in order to provide better recommendation for media items such as movies or TV shows. As part of this paper we develop a new paradigm for incorporating the feedback of the user’s friends. A field study that was conducted on real subjects indicates the strengths and the weaknesses of the proposed method compared to other simple and classic methods. The system is envisioned to function as a service for recommending personalized media (audio, video, print) on mobile phones, online media portals, sling boxes, etc. It is currently under development within Deutsche Telekom Laboratories - Innovations of Integrated Communication projects.
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Ben-Shimon, D., Tsikinovsky, A., Rokach, L., Meisles, A., Shani, G., Naamani, L. (2007). Recommender System from Personal Social Networks. In: Wegrzyn-Wolska, K.M., Szczepaniak, P.S. (eds) Advances in Intelligent Web Mastering. Advances in Soft Computing, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72575-6_8
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DOI: https://doi.org/10.1007/978-3-540-72575-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72574-9
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