[PDF.36rs] Recommender Systems and the Social Web: Leveraging Tagging Data for Recommender Systems

Recommender Systems and the Social Web: Leveraging Tagging Data for Recommender Systems

[PDF.du19] Recommender Systems and the Social Web: Leveraging Tagging Data for Recommender Systems

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 | #2006332 in Books |  Springer Vieweg |  2013-04-10 |  2013-04-10 | Original language:English | PDF # 1 |  8.27 x.30 x5.83l,.35 | File type: PDF | 112 pages

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|| ||From the reviews:|“This book presents the results of research conducted in the course of a doctoral study on improving recommendations on the web. … I recommend this book to graduate students and researchers in the field of recommender systems an

​There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched the social dimension of the Web. As user-provided content data also tells us something about the user, one can learn the user’s individual preferences from the Social Web...

You can specify the type of files you want, for your gadget.Recommender Systems and the Social Web: Leveraging Tagging Data for Recommender Systems   |  Fatih Gedikli.Not only was the story interesting, engaging and relatable, it also teaches lessons.

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