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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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