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Titlebook: Social Media Modeling and Computing; Steven C.H. Hoi,Jiebo Luo,Irwin King Book 2011 Springer-Verlag London Limited 2011 Data Mining.Machin

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书目名称Social Media Modeling and Computing
编辑Steven C.H. Hoi,Jiebo Luo,Irwin King
视频video
概述Presents contributions from an international selection of preeminent experts in the field.Discusses topics on social-media content analysis, and examines social-media system design and analysis.Descri
图书封面Titlebook: Social Media Modeling and Computing;  Steven C.H. Hoi,Jiebo Luo,Irwin King Book 2011 Springer-Verlag London Limited 2011 Data Mining.Machin
描述This timely text/reference presents the latest advances in various aspects of social media modeling and social media computing research. Gathering together superb research from a range of established international conferences and workshops, the editors coherently organize and present each of the topics in relation to the basic principles and practices of social media modeling and computing. Individual chapters can be also be used as self-contained references on the material covered. Topics and features: presents contributions from an international selection of preeminent experts in the field; discusses topics on social-media content analysis; examines social-media system design and analysis, and visual analytic tools for event analysis; investigates access control for privacy and security issues in social networks; describes emerging applications of social media, for music recommendation, automatic image annotation, and the analysis and improvement of photo-books.
出版日期Book 2011
关键词Data Mining; Machine Learning; Multimedia; Social Networks; Tagging; Web 2; 0
版次1
doihttps://doi.org/10.1007/978-0-85729-436-4
isbn_softcover978-1-4471-5936-0
isbn_ebook978-0-85729-436-4
copyrightSpringer-Verlag London Limited 2011
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Steven C.H. Hoi,Jiebo Luo,Irwin KingPresents contributions from an international selection of preeminent experts in the field.Discusses topics on social-media content analysis, and examines social-media system design and analysis.Descri
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Quantifying Visual-Representativeness of Social Image Tags Using Image Tag Claritywe show that the image tag clarity score can effectively identify the visual-representative tags from all tags contributed by users. Based on the tag clarity scores, we have made a few interesting observations that could be used to support many tag-based applications.
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Using Rich Social Media Information for Music Recommendation via Hypergraph Modelendation as a ranking problem on this hypergraph. While an edge of an ordinary graph connects only two objects, a hyperedge represents a set of objects. In this way, hypergraph can be naturally used to model high-order relations.
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