From Security to Community Detection in Social Networking Platforms

Nonfiction, Computers, Database Management, General Computing, Social & Cultural Studies, Social Science
Cover of the book From Security to Community Detection in Social Networking Platforms by , Springer International Publishing
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Author: ISBN: 9783030112868
Publisher: Springer International Publishing Publication: April 9, 2019
Imprint: Springer Language: English
Author:
ISBN: 9783030112868
Publisher: Springer International Publishing
Publication: April 9, 2019
Imprint: Springer
Language: English

This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. 

The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. 

The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.

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