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Learning Automata Approach for Social Networks: 820 (Studies in Computational Intelligence, 820) - Tapa dura

Libro 325 de 538: Studies in Computational Intelligence

Rezvanian, Alireza; Moradabadi, Behnaz; Ghavipour, Mina

 
9783030107666: Learning Automata Approach for Social Networks: 820 (Studies in Computational Intelligence, 820)
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ISBN 10: 3030107663 ISBN 13: 9783030107666
Editorial: Springer, 2019

Sinopsis

This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions among individuals and in the networks’ evolution, and to develop the algorithms required for meaningful analysis.

As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.

"Sinopsis" puede pertenecer a otra edición de este libro.

De la contraportada

This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions among individuals and in the networks evolution, and to develop the algorithms required for meaningful analysis.

As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2019
Idioma
Inglés
ISBN 10 
3030107663
ISBN 13 
9783030107666
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
348
Contacto del fabricante
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Darmstadt
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Alemania

Otras ediciones populares con el mismo título

9783030107680: Learning Automata Approach for Social Networks

Edición Destacada

ISBN 10:  303010768X ISBN 13:  9783030107680
Editorial: Springer, 2019
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