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Recommender Systems and the Social Web
Fatih Gedikli
€ 70.31
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Description for Recommender Systems and the Social Web
Paperback. Num Pages: 112 pages, 15 black & white illustrations, 14 colour illustrations, 28 black & white tables, biograp. BIC Classification: UNF; UNH; UYZG. Category: (P) Professional & Vocational. Dimension: 210 x 148 x 10. Weight in Grams: 173.
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. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of how user-provided tagging data can be ... Read more
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. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of how user-provided tagging data can be ... Read more
Product Details
Format
Paperback
Publication date
2013
Publisher
Springer Fachmedien Wiesbaden Germany
Number of pages
112
Condition
New
Number of Pages
112
Place of Publication
Weisbaden, Germany
ISBN
9783658019471
SKU
V9783658019471
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Fatih Gedikli
Dr. Fatih Gedikli is a research assistant in computer science at TU Dortmund, Germany.
Reviews for Recommender Systems and the Social Web
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 and the social web. It can also serve as inspiration on how to conduct user studies for evaluating various ... Read more