Next Generation Data Technologies for Collective Computational Intelligence

by Bessis, Nik; Xhafa, Fatos

• ISBN13: 9783642203435
• ISBN10: 3642203434
• Format: Hardcover
• Copyright: 2011-04-30
• Publisher: Springer-Verlag New York Inc

Summary

This book focuses on next generation data technologies in support of collective and computational intelligence. The book brings various next generation data technologies together to capture, integrate, analyze, mine, annotate and visualize distributed data #xE2;#xAC;#x1C; made available from various community users #xE2;#xAC;#x1C; in a meaningful and collaborative for the organization manner. A unique perspective on collective computational intelligence is offered by embracing both theory and strategies fundamentals such as data clustering, graph partitioning, collaborative decision making, self-adaptive ant colony, swarm and evolutionary agents. It also covers emerging and next generation technologies in support of collective computational intelligence such as Web 2.0 social networks, semantic web for data annotation, knowledge representation and inference, data privacy and security, and enabling distributed and collaborative paradigms such as P2P, Grid and Cloud Computing due to the geographically dispersed and distributed nature of the data. The book aims to cover in a comprehensive manner the combinatorial effort of utilizing and integrating various next generations collaborative and distributed data technologies for computational intelligence in various scenarios. The book also distinguishes itself by assessing whether utilization and integration of next generation data technologies can assist in the identification of new opportunities, which may also be strategically fit for purpose.

Table of Contents

Foundations and Principles
Coordination Mechanisms in Complex Software Systems	p. 3
Ant Colony Optimization and Data Mining	p. 31
OpenSEA: A Framework for Semantic Interoperation between Enterprises	p. 61
Building Collective Tag Intelligence through Folksonomy Coordination	p. 87
Trust-Based Techniques for Collective Intelligence in Social Search Systems	p. 113
Advanced Models and Practices
Visualising Computational Intelligence through Converting Data into Formal Concepts	p. 139
Constructing Ensemble Classifiers from GEP-Induced Expression Trees	p. 167
Self-Organized Load Balancing through Swarm Intelligence	p. 195
Computational Intelligence in Future Wireless and Mobile Communications by Employing Channel Prediction Technology	p. 225
Decision Making under Synchronous Time Stress among Bilateral Decision Makers	p. 251
Augmenting Human Intelligence in Goal Oriented Tasks	p. 271
Advanced Applications
Clouds and Continuous Analytics Enabling Social Networks for Massively Multiplayer Online Games	p. 303
Adaptive Fuzzy Inference Neural Network System for EEG and Stabilometry Signals Classification	p. 329
Demand on Computational Intelligence Paradigms Synergy: SOA and Mobility for Efficient Management of Resource-Intensive Applications on Constrained Devices	p. 357
Evolutionary Algorithms towards Generating Entertaining Games	p. 383
Leveraging Massive User Contributions for Knowledge Extraction	p. 415
Validating Privacy Requirements in Large Survey Rating Data	p. 445
Future Trends and Concepts
Next Generation Service Delivery Network as Enabler of Applicable Intelligence in Decision and Management Support Systems: Migration Strategies, Planning Methodologies, Architectural Design Principles	p. 473
Utilizing Next Generation Emerging Technologies for Enabling Collective Computational Intelligence in Disaster Management	p. 503
Emerging, Collective Intelligence for Personal, Organisational and Social Use	p. 527
Mobile Sensing Technologies and Computational Methods for Collective Intelligence	p. 575
ICT and Dataveillance	p. 599
Index	p. 625
Author Index	p. 637
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