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

饥荒

Book 2011estigates 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.

ornithology

Book 2011ether 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-containe

maladorit

独轮车

Quantifying Visual-Representativeness of Social Image Tags Using Image Tag Clarity the nature of tagging, many tags associated with images are not visually descriptive. In this chapter, we propose . to evaluate the effectiveness of a tag in describing the visual content of its annotated images, which is also known as the image tag visual-representativeness. It is measured by comp

思想上升

Tag-Based Social Image Search: Toward Relevant and Diverse Resultsnterest on these websites. However, the existing ranking methods for tag-based image search frequently return results that are irrelevant or lack of diversity. This chapter presents a diverse relevance ranking scheme which simultaneously takes relevance and diversity into account by exploring the co

高尔夫

放纵

Combining Multi-modal Features for Social Media Analysisalysis process where specialized techniques are used to overcome the obstacles arising from the heterogeneity of data. Focusing at the optimal combination of low-level features (i.e., early fusion), we present a bio-inspired algorithm for feature selection that weights the features based on their ap

细胞膜

Multi-label Image Annotation by Structural Grouping Sparsitymented to describe their various aspects of visual characteristics, such as color, texture and shape etc. The heterogeneous features are often over-complete to describe certain semantic. Therefore, the selection of limited discriminative features for certain semantics is hence crucial to make the im

obligation

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