Advances in Intelligent Networking and Collaborative Systems by Barolli, Leonard; Miwa, Hiroyoshi; Natwichai, Juggapong;

Hosszú leírás:

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With the fast Internet development, we are experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm, which locates people at the very centre of networks and exploits the value of people's connections, relations and collaboration. Social Networks are also playing a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems.

Virtual campuses, Virtual Communities and organizations strongly leverage Intelligent Networking and Collaborative Systems by a great variety of formal and informal electronic relations, such as business-to-business, peer-to-peer and many types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and in an autonomous way. In addition, powerful technologies based on Cloud Computing are currently enhancing collaborative and networking applications but also facing new issues and challenges. The principal purpose of the research and development community is to stimulate research that will lead to the creation of responsive environments for networking and, at longer-term, the development of adaptive, secure, mobile, and intuitive intelligent systems for collaborative work and learning.

The aim of the volume “Advances on Intelligent Networking and Collaborative Systems” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems and secure intelligent cloud systems as well as to reveal synergies among various paradigms in such a multi-disciplinary field of intelligent collaborative systems.

Tartalomjegyzék:

Investigating the Effect of Cluster Structure on the Effectiveness of Eigenvalue Manipulation Based on Matrix Perturbation Theory.- Study on the Important Eigenvalues and Eigenvectors Based on Low-Rank Approximation with Graph Spectrum Shift.- Consideration of a Method Using Degree-Biased Random Walk to Estimate Important Eigenvalues of Graph Matrices.- An Integrated Computational Approach to improve Online Debates Understanding.