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Computational Social Networks: Mining and Visualization

ISBN-13: 9781447162377 / Angielski / Miękka / 2014 / 386 str.

Ajith Abraham
Computational Social Networks: Mining and Visualization Abraham, Ajith 9781447162377 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Computational Social Networks: Mining and Visualization

ISBN-13: 9781447162377 / Angielski / Miękka / 2014 / 386 str.

Ajith Abraham
cena 403,47 zł
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This book is the third of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on knowledge discovery and visualization of complex networks (the other two volumes review Tools, Perspectives, and Applications, and Security and Privacy in CSNs). Topics and features: presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage from a better understanding of complex social networks; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, highlighting methods for the data mining of CSNs; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.

Kategorie:
Informatyka
Kategorie BISAC:
Computers > Networking - Hardware
Computers > Database Administration & Management
Computers > User Interfaces
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9781447162377
Rok wydania:
2014
Wydanie:
2012
Ilość stron:
386
Waga:
0.61 kg
Wymiary:
23.5 x 15.5
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

Part I: Mining

Social Networks Analysis: Tools, Measures and Visualization
Neveen Ghali, Mrutyunjaya Panda, Aboul Ella Hassanien, Ajith Abraham and Vaclav Snasel

Performance Evaluation of Social Network Using Data Mining Techniques
Mrutyunjaya Panda, Ajith Abraham, Satchidananda Dehuri and Manas Ranjan Patra

Bio-Inspired Clustering and Data Diffusion in Machine Social Networks
Iva Bojic, Tomislav Lipic and Vedran Podobnik

Mining Geo-Referenced Community-Contributed Multimedia Data
Milan Mirkovic, Dubravko Culibrk and Vladimir Crnojevic

Correlation Mining for Web News Retrieval
Jing Liu, Zechao Li and Lu Hanqing

Mining Micro-Blogs: Opportunities and Challenges
Yang Liao, Masud Moshtaghi, Bo Han, Shanika Karunasekera, Ramamohanarao Kotagiri, Timothy Baldwin, Aaron Harwood and Philippa Pattison

Mining Buyer Behavior Patterns Based on Dynamic Group-Buying Networks
Xiao Liu and Jianmei Yang

Reliable Online Social Network Data Collection
Fehmi Ben Abdesslem, Iain Parris and Tristan Henderson

Knowledge Mining from the Twitter Social Network: The Case of Barack Obama
Marco Guidi, Igor Ruiz-Agundez and Izaskun Canga-Sanchez

Part II: Visualization

Mining and Visualizing Research Networks using the Artefact-Actor-Network Approach
Wolfgang Reinhardt, Adrian Wilke, Matthias Moi, Hendrik Drachsler and Peter Sloep

Intelligent Visual Pattern Clustering for Storage Layouts in Virtual Environments
Shao-Shin Hung, Chih Ming Chiu, Tsou Tsun Fu, Jung Tzung Chen and Jyh-Jong Tsay

Salvatore Catanese, Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara and Alessandro Provetti

Analysis of Human-Computer Interactions and Online Social Networking: A Framework
Liguo Yu and Dr. Srini Ramaswamy

Implementation of Social Network Analysis for Web Cache Content Mining Visualization
Sarina Sulaiman, Siti Mariyam Shamsuddin and Ajith Abraham

Dr. Ajith Abraham is Director of the Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference of Computational Aspects of Social Networks (CASoN), Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (since 2008), and a Distinguished Lecturer of the IEEE Computer Society representing Europe (since 2011).

The study of computational social networks (CSNs) is an emerging interdisciplinary field, concerned with the intersection of social behavior and computer systems.

Due to the dynamic and ever-evolving nature of social networks, it can be difficult to comprehend the connections and influence between users. However, visualization techniques can aid the understanding of how these networks function. This comprehensive text/reference is the third of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, with a specific focus on knowledge discovery and visualization of complex networks (the other two volumes review Tools, Perspectives, and Applications, and Security and Privacy in CSNs).

Topics and features:

  • Includes a thorough introduction to this exciting and blossoming field
  • Presents the latest advances in CSNs, and illustrates how organizations can gain a competitive advantage from a better understanding of complex social networks
  • Discusses the design and use of a wide range of computational tools and software for social network analysis
  • Describes simulations of social networks, and the representation and analysis of social networks, highlighting methods for the data mining of CSNs
  • Provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology

This authoritative work is a useful resource for researchers and developers involved in social network research and related issues. Postgraduate and senior undergraduate students will also find this a valuable reference for courses on CSNs.



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