Overview
- Highlights recent advances in social network analysis
- Presents problems addressed by learning automata theory
- Includes topics concerning network centralities, models, problems, theories, algorithms, and their applications
Part of the book series: Studies in Computational Intelligence (SCI, volume 820)
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Table of contents (9 chapters)
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Front Matter
Keywords
About this book
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.Authors and Affiliations
Bibliographic Information
Book Title: Learning Automata Approach for Social Networks
Authors: Alireza Rezvanian, Behnaz Moradabadi, Mina Ghavipour, Mohammad Mehdi Daliri Khomami, Mohammad Reza Meybodi
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-030-10767-3
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-10766-6Published: 31 January 2019
eBook ISBN: 978-3-030-10767-3Published: 22 January 2019
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVII, 329
Number of Illustrations: 35 b/w illustrations, 72 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Social Media