Cross-Network Social Multimedia Computing

  • Jitao SangEmail author
Part of the Springer Theses book series (Springer Theses)


Social multimedia contributes significantly to the arrival of the Big Data era. The distribution of social multimedia content and users’ social multimedia activities among various social media networks motivate us to investigate social multimedia computing under the cross-network circumstances. We interpret cross-network as the “variety” of social multimedia: the heterogeneous data in various social media networks. In this chapter, basic tasks of user-centric social multimedia computing are extended under the cross-network circumstances, by exploiting the overlapped users among social media networks.


Social Networking Site Latent Dirichlet Allocation Topic Distribution Normalize Discount Cumulative Gain Social Media Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.National Lab of Pattern Recognition, Institute of AutomationChinese Academy of SciencesBeijingChina

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