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Online Social Media Content Delivery - Zhi Wang, Wenwu Zhu, Shiqiang Yang

Online Social Media Content Delivery

A Data-Driven Approach
Buch | Softcover
109 Seiten
2018 | 2018 ed.
Springer Verlag, Singapore
978-981-10-2773-4 (ISBN)
CHF 82,35 inkl. MwSt
This book explains how to use a data-driven approach to design strategies for social media content delivery. Secondly, the book describes data-driven models to capture information diffusion in online social networks and social media content propagation and popularity, before presenting prediction models for social media content delivery.
This book explains how to use a data-driven approach to design strategies for social media content delivery. It first introduces readers to how social information can be effectively gathered for big data analysis, which provides content delivery intelligence. Secondly, the book describes data-driven models to capture information diffusion in online social networks and social media content propagation and popularity, before presenting prediction models for social media content delivery. By addressing the resource allocation and content replication aspects of social media content delivery, the book presents the latest data-driven strategies. In closing, it outlines a number of potential research directions regarding social media content delivery.

Dr. Zhi Wang received his B.E. and Ph.D. degrees in Computer Science in 2008 and 2014, respectively, both from Tsinghua University, Beijing, China. He is currently an assistant professor at Tsinghua University. His research areas include online social networks, mobile cloud computing and large-scale multimedia systems. He received the China Computer Federation Outstanding Doctoral Dissertation Award (2014), ACM Multimedia Best Paper Award (2012), and MMM Best Student Paper Award (2015). Prof. Wenwu Zhu received his Ph.D. degree in Electrical and Computer Engineering from New York University Polytechnic School of Engineering in 1996. He currently works at Tsinghua University’s Computer Science Department as a professor under China’s “1000 Talent Plan.” His current research interests are in multimedia cloud computing, social media computing, multimedia big data, and multimedia communications and networking. He has served or serves on various editorial boards, such as Guest Editor for the Proceedings of the IEEE, IEEE T-CSVT, and IEEE JSAC; Associate Editor for IEEE Transactions on Mobile Computing, IEEE Transactions on Multimedia, and IEEE Transactions on Circuits and Systems for Video Technology; and Leading Editor of the Area “Computer Networks and Distributed Computing” for the Journal of Computer Science and Technology. He received the Best Paper Award in ACM Multimedia 2012, the Best Paper Award in IEEE Transactions on Circuits and Systems for Video Technology in 2001, and four other international Best Paper Awards. He is an IEEE Fellow, SPIE Fellow, and ACM Distinguished Scientist. Prof. Shiqiang Yang received his B.E. and M.E. degrees in computer science from Tsinghua University, Beijing, China in 1977 and 1983, respectively. From 1980 to 1992, he worked as an assistant professor at Tsinghua University. He was an associate professor from 1994 to 1999, and has served as a professor since 1999. From 1994 to 2011, he worked as the associate head of Tsinghua University’s Department of Computer Science and Technology. He is currently President of the Multimedia Committee of China Computer Federation, Beijing, and co-director of Tsinghua University’s Microsoft-Tsinghua Multimedia Joint Lab. His primary research interests include multimedia procession, media streaming and online social networks.

Introduction.- Social Media Big Data.- Social Propagation and Social Popularity.- Social Media Content Delivery.- Conclusion and Future Research Directions.

Erscheinungsdatum
Reihe/Serie SpringerBriefs in Computer Science
Zusatzinfo 64 Illustrations, black and white; XI, 109 p. 64 illus.
Verlagsort Singapore
Sprache englisch
Maße 155 x 235 mm
Themenwelt Mathematik / Informatik Informatik Datenbanken
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Sozialwissenschaften
Schlagworte Big Data • Content Delivery Network • Edge network • online social network • Social Media • Social Media Content Delivery • Social Networks • Social propagation
ISBN-10 981-10-2773-0 / 9811027730
ISBN-13 978-981-10-2773-4 / 9789811027734
Zustand Neuware
Informationen gemäß Produktsicherheitsverordnung (GPSR)
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