Machine Learning in Complex Networks

This book explores the features and advantages offered by complex networks in the domain of machine learning. In the first part of the book, we present an overview on complex networks and machine learning. Then, we provide a comprehensive description on n

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achine Learning in Complex Networks

Machine Learning in Complex Networks

Thiago Christiano Silva • Liang Zhao

Machine Learning in Complex Networks

123

Liang Zhao Computer Science and Mathematics University of São Paulo (USP) Ribeirão Preto, São Paulo, Brazil

Thiago Christiano Silva Departament of Research (Depep) Central Bank of Brazil Brasília, Distrito Federal, Brazil

ISBN 978-3-319-17289-7 DOI 10.1007/978-3-319-17290-3

ISBN 978-3-319-17290-3 (eBook)

Library of Congress Control Number: 2015958893 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www. springer.com)

To my wife Ester Cordeiro Silva. To my daughter Yasmin Christiane Silva. To my mother Ivonilde Aparecida Paina Silva. To my father Francisco Merquiades Silva. Thiago Christiano Silva To my wife Sandra Regina Fuzaro Zhao. To my son Wellington Yuanhe Zhao. 献给我的父亲赵贯民和母亲古怀玉 Liang Zhao

Preface

Machine learning stands as an important research area that aims at developing computational methods capable of improving their performances with previously acquired experiences. Although a large amount of machine learning techniques has been proposed and successfully applied in real systems, there are still many challenging issues that need to be addressed. In the last years, an increasing interest in techniques based on complex networks (large-scale graphs with nontrivial connection patterns) has been verified. This emergence is explained by the inherent advantages that the data representation as networks provides. They allow for capturing spatial, topological, and functional relations of the data. This book presents the features and possible advantages offered by complex networks in the machine learning domain. In the first part, we give an introduction to the machine learning and complex netwo