Social Network-Based Recommender Systems

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Social Network,Recommender Systems,基于社交网络的推荐系统
Daniel schall Social network-Based Recommender Systems ② Springer Daniel schall Siemens Corporate Technology Wien. austria ISBN978-3-319227344 ISBN978-3-319-22735-1( e Book) DOI10.10071978-3-319-22735-1 Library of Congress Control Number: 2015951351 Springer Cham Heidelberg New York Dordrecht London O Springer International Publishing Switzerland 2015 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 pap Springer International Publishing AG Switzerland is part of Springer Science+Business Media(www springer. com) To my son kilian Preface People increasingly use social networks to manage various aspects of their lives such as communication, collaboration, and information sharing. A user's network of friends may offer a wide range of important benefits such as receiving online help and support and the ability to exploit professional opportunities. One of the most profound properties of social networks is their dynamic nature governed by people constantly joining and leaving the social networks. The circle of friends may frequently change when people establish friendship through social links or when their interest in a social relationship ends and the link is removed This book introduces novel techniques and algorithms for social network-based recommender systems. Here, concepts such as link prediction using graph patterns following recommendation based on user authority, strategic partner selection in collaborative systems, and network formation based on social brokers"are presented In this book, well-established graph models such as the notion of hubs and authorities provide the basis for authority-based recommendation and are systematically extended towards a unified Hyperlink Induced Topic Search(HITS) and personalized pageRank model detailed experiments using various real-world datasets and systematic evaluation of recommendation results proof the applicability of the presented concepts Vienna. austria Daniel schall June 2015 Acknowledgements This book provides a detailed summary and new viewpoints on the author's research in the field of social network analysis and link formation techniques. Daniel Schall received his Ph D. degree in computer science from the Vienna University of Technology in 2009 He started his research career at Siemens Corporate Research in Princeton, NJ, USA, in 2003, where he was employed as a technical associate. In 2006, he began his doctoral studies at the vienna University of Technology. At the vienna Univer- sity of Technology, he was involved in a number of European funded FP6 and FP7 projects both as a project manager and key researcher. Daniel was a principal inves tigator of crowdsourcing and social computing activities at the distributed systems Group The main results of his research in the context of crowdsourcing and Human Provided services were published in the book Service-Oriented Crowdsourcing: Architecture, Protocols and algorithms. Also, he published more than 40 scientific papers at top-ranked international conferences and more than 20 scientific journal papers in highly ranked journals and renowned magazines including the Journal of Informetrics, Decision Support Systems, Data and Knowledge Engineering, Information Systems, IEEE Transactions on Services Computing, IEEE Computer, IEEE Internet Computing, and Social Network Analysis and Mining Dr Daniel Schall is currently employed as a senior key expert research scientist at Siemens Corporate Technology in Vienna, Austria

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