| 書目名稱 | Learning Automata Approach for Social Networks | | 編輯 | Alireza Rezvanian,Behnaz Moradabadi,Mohammad Reza | | 視頻video | http://file.papertrans.cn/583/582689/582689.mp4 | | 概述 | Highlights recent advances in social network analysis.Presents problems addressed by learning automata theory.Includes topics concerning network centralities, models, problems, theories, algorithms, a | | 叢書名稱 | Studies in Computational Intelligence | | 圖書封面 |  | | 描述 | .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. | | 出版日期 | Book 2019 | | 關鍵詞 | Social Networks; Complex Social Networks; Stochastic Graph; Learning Automata; Social Network Analysis; L | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-10767-3 | | isbn_ebook | 978-3-030-10767-3Series ISSN 1860-949X Series E-ISSN 1860-9503 | | issn_series | 1860-949X | | copyright | Springer Nature Switzerland AG 2019 |
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