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

Author: Fatih Gedikli
Publisher: Wiesbaden : Springer Vieweg, 2013.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Publication:Recommender systems and the social web.
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Printed edition
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Fatih Gedikli
ISBN: 9783658019488 3658019484 9783658019471 3658019476
OCLC Number: 1058600562
In: Gedikli, Fatih
Language Note: English.
Notes: Description based upon print version of record.
Description: Online-Ressource (XI, 112 p. 29 illus., 14 illus. in color, digital)
Contents: Recommender Systems --
Social Tagging --
Algorithms --
Explanations.
Other Titles: Recommender Systems and the Social Web
Responsibility: by Fatih Gedikli.

Abstract:

There is an increasing demand for recommender systems due to the information overload users are facing on the Web. A tag recommender algorithm is proposed which recommends tags for users to annotate  Read more...

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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 Read more...

 
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