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Record Nr. |
UNINA9910299858403321 |
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Autore |
Roy Suman Deb |
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Titolo |
Social Multimedia Signals : A Signal Processing Approach to Social Network Phenomena / / by Suman Deb Roy, Wenjun Zeng |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (181 p.) |
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Disciplina |
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Soggetti |
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Signal processing |
Image processing |
Speech processing systems |
Input-output equipment (Computers) |
Computational intelligence |
Industrial management |
Signal, Image and Speech Processing |
Input/Output and Data Communications |
Computational Intelligence |
Media Management |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 |
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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. |
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