Social Multimedia Signals: A Signal Processing Approach to Social Network Phenomena
Autor Suman Deb Roy, Wenjun Zengen Limba Engleză Hardback – 27 aug 2014
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Specificații
ISBN-13: 9783319091167
ISBN-10: 3319091166
Pagini: 186
Ilustrații: X, 176 p. 95 illus., 79 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.44 kg
Ediția:2015
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3319091166
Pagini: 186
Ilustrații: X, 176 p. 95 illus., 79 illus. in color.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.44 kg
Ediția:2015
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
Web 2.x.- Media on the Web.- The World of Signals.- The Network and the Signal.- Detection - Needle in a Haystack.- Estimation – The Empirical Judgment.- Following Signal Trajectories.- Capturing Cross-Domain Ripples.- Socially-aware Media Applications.- Revelations from Social Multimedia Data.- Socio-Semantic Analysis.- Data Visualization: Gazing at Ripples.
Notă biografică
Dr. Suman Deb Roy is a Data Scientist with Betaworks, NY Dr. Wenjun (Kevin) Zeng is a Professor at the Computer Science Dept. with the Univ. of Missouri, Columbia, MO, USA.
Textul de pe ultima copertă
Social Multimedia Signals is intended for those whose interest is to study the Social Web and develop automated tools to analyze it better. It is especially useful for researchers experienced with signal processing or multimedia analysis but have little exposure to social networks and social multimedia data. Those new to social multimedia should find the first chapters extremely useful to get a thorough look at how social data behaves. Conversely, social scientists should find useful the authors’ introduction to several signal processing techniques that can be employed to manipulate large-scale social data. For those new to signal processing, Chapters 5, 6 and 7 will get readers underway with basic techniques for signal processing from social multimedia. Later chapters include a significant amount of material on machine learning for those interested in intelligent algorithms for the Social Web. The authors wrote this book in a balanced fashion, for multimedia researchers, social scientists, network scientists, data scientists who work with social web data, and professionals who use social media on a daily basis.
· Explores how media popularity in one domain is determined by another domain;
· Presents a granular look at social networks: micro, meso, and macro;
· Examines finding hidden communities in social networks based on shared multimedia.
· Explores how media popularity in one domain is determined by another domain;
· Presents a granular look at social networks: micro, meso, and macro;
· Examines finding hidden communities in social networks based on shared multimedia.
Caracteristici
Explores how media popularity in one domain is determined by another domain Presents a granular look at social networks: micro, meso and macro Examines finding hidden communities in social networks based on shared multimedia Includes supplementary material: sn.pub/extras