Recommender Systems for Social Tagging Systems. 1st ed. 2012

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電子ブック

責任表示:

by Leandro Balby Marinho, Andreas Hotho, Robert Jäschke, Alexandros Nanopoulos, Steffen Rendle, Lars Schmidt-Thieme, Gerd Stumme, Panagiotis Symeonidis

出版情報:

New York, NY : Springer New York : Imprint: Springer, 2012

著者名:

Balby Marinho, Leandro.

Hotho, Andreas.

Jäschke, Robert.

Nanopoulos, Alexandros.

Rendle, Steffen.

Schmidt-Thieme, Lars.

Stumme, Gerd.

Symeonidis, Panagiotis.

SpringerLink (Online service)

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シリーズ名:

SpringerBriefs in Electrical and Computer Engineering ;

ISBN:

9781461418948 [1461418941]    

注記:

Social Tagging Systems -- Recommender Systems -- Baseline Techniques -- Advanced Techniques -- Offline Evaluation -- Real World Social Tagging Recommender Systems -- Online Evaluation -- Conclusions.
Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable metho

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