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Recommender Systems: An Introduction Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich
Publisher: Cambridge University Press

EMusic, the second largest online music store after iTunes, introduced a new recommendation system on its site late last year. On the other hand, recommender systems can significantly affect the success of social media websites, ensuring each user is presented with the most attractive and relevant content, on a personal basis. Recommender systems are fast becoming as standard a tool as search engines, helping users to discover content that interests them with very little effort. We also illustrate specific computational models that have been proposed for mobile recommender systems and we close the paper by presenting some possible future developments and extension in this area. This is a youtube clip that gives you a simple introduction about how Netflix uses the collaborative filtering recommender system to improve their business. Under this circumstance, researchers introduced recommender systems in early 1990s. This webinar provides an introduction to recommender systems, describing the different types of recommendation technologies available and how they are used in different applications today. In their early stage, recommender systems only focused on pure information filtering field. 13:00 – 13:30 – Opening and Introduction. It conveys some simple ideas and is worth a look. 9:30 Introductions – all participants introduce themselves. Tags, comments, votes, and explicit people relationships, which can be used to enhance recommendations. See schedule below (detailed schedule here: http://cslinux0.comp.hkbu.edu.hk/~fwang/srs2013/?page_id=79.