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Recommender System from Personal Social Networks

  • David Ben-Shimon
  • Alexander Tsikinovsky
  • Lior Rokach
  • Amnon Meisles
  • Guy Shani
  • Lihi Naamani
Part of the Advances in Soft Computing book series (AINSC, volume 43)

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.

Keywords

Social Network Recommender System Collaborative Filter Personal Network Recommendation List 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • David Ben-Shimon
    • 1
  • Alexander Tsikinovsky
    • 1
  • Lior Rokach
    • 2
  • Amnon Meisles
    • 3
  • Guy Shani
    • 3
  • Lihi Naamani
    • 2
  1. 1.Deutsche Telekom Laboratories at Ben-Gurion University 
  2. 2.Department of Information System Engineering, Ben-Gurion University 
  3. 3.Department of Computer Science, Ben-Gurion University 

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