Social Networks: A Framework of Computational Intelligence

Pedrycz, Witold|Chen, Shyi-Ming

ISBN 10: 3319374877 / ISBN 13: 9783319374871

Published by Springer International Publishing, 2016

About this Item

Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers introductory chapters both in terms of social networks, graph theory and specialized introduction to Computational IntelligenceSelf-contained book easily accessible to a broad audienceSystematic exposure of the concepts, design metho. Seller Inventory # 385704239

Bibliographic Details

Title: Social Networks: A Framework of ...

Publisher: Springer International Publishing

Publication Date: 2016

Binding: Soft cover

Condition: New

About this title

Synopsis:

This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms. The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling. Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social networks, business intelligence and forming collaboration schemes.

Given the subject area, this book is aimed at a broad audience of researchers and practitioners. Owing to the nature of the material being covered and a way it is organized, the volume will appeal to the well-established communities including those active in various disciplines in which social networks, their analysis and optimization are of genuine relevance. Those involved in operations research, management, various branches of engineering, and economics will benefit from the exposure to the subject matter.