Next Generation Data Technologies for Collective Computational Intelligence

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 – made available from various community use...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Bessis, Nik (Επιμελητής έκδοσης), Xhafa, Fatos (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Σειρά:Studies in Computational Intelligence, 352
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Next Generation Data Technologies for Collective Computational Intelligence  |h [electronic resource] /  |c edited by Nik Bessis, Fatos Xhafa. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2011. 
300 |a XVIII, 638 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 352 
505 0 |a Part I: Foundations and Principles -- Part II: Advanced Models and Practices -- Part III: Advanced Applications Section IV: Future Trends and Concepts. 
520 |a 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 – made available from various community users – 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. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Computational intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Information Systems Applications (incl. Internet). 
700 1 |a Bessis, Nik.  |e editor. 
700 1 |a Xhafa, Fatos.  |e editor. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642203435 
830 0 |a Studies in Computational Intelligence,  |x 1860-949X ;  |v 352 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-20344-2  |z Full Text via HEAL-Link 
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950 |a Engineering (Springer-11647)