Optimal Social Influence (SpringerBriefs in Optimization) - Softcover

Buch 37 von 43: SpringerBriefs in Optimization

Xu, Wen; Wu, Weili

 
9783030377748: Optimal Social Influence (SpringerBriefs in Optimization)

Inhaltsangabe

This self-contained book describes social influence from a computational point of view, with a focus on recent and practical applications, models, algorithms and open topics for future research. Researchers, scholars, postgraduates and developers interested in research on social networking and the social influence related issues will find this book useful and motivating. The latest research on social computing is presented along with and illustrations on how to understand and manipulate social influence for knowledge discovery by applying various data mining techniques in real world scenarios. Experimental reports, survey papers, models and algorithms with specific optimization problems are depicted. The main topics covered in this book are: chrematistics of social networks, modeling of social influence propagation, popular research problems in social influence analysis such as influence maximization, rumor blocking, rumor source detection, and multiple social influence competing.  

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Über die Autorin bzw. den Autor

Wen Xu is an Assistant Professor of Chinese Language Education at Shanghai Jiao Tong University. Her research interests focus on the intersection of language, education and society. Currently, her research projects and publications encompass studies of international students' lived experiences in China.

Von der hinteren Coverseite

This self-contained book describes social influence from a computational point of view, with a focus on recent and practical applications, models, algorithms and open topics for future research. Researchers, scholars, postgraduates and developers interested in research on social networking and the social influence related issues will find this book useful and motivating. The latest research on social computing is presented along with and illustrations on how to understand and manipulate social influence for knowledge discovery by applying various data mining techniques in real world scenarios. Experimental reports, survey papers, models and algorithms with specific optimization problems are depicted. The main topics covered in this book are: chrematistics of social networks, modeling of social influence propagation, popular research problems in social influence analysis such as influence maximization, rumor blocking, rumor source detection, and multiple social influence competing.  

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