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Social Networks: A Framework of Computational Intelligence [electronic resource] / edited by Witold Pedrycz, Shyi-Ming Chen.

Contributor(s): Pedrycz, Witold [editor.] | Chen, Shyi-Ming [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 526Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: XI, 440 p. 168 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319029931.Subject(s): Engineering | Artificial intelligence | Computational intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics)Additional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
From the Contents: Detecting Community Structures in Networks Using A Linear-Programming Based Approach -- Personalization of Social Networks: Adaptive Semantic Layer Approach -- Social Network and Formal Concept Analysis -- Explaining Variation in State Involvement in Cyber Attacks: A Social Network Approach.
In: Springer eBooksSummary: 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. .
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From the Contents: Detecting Community Structures in Networks Using A Linear-Programming Based Approach -- Personalization of Social Networks: Adaptive Semantic Layer Approach -- Social Network and Formal Concept Analysis -- Explaining Variation in State Involvement in Cyber Attacks: A Social Network Approach.

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. .

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