Recommender Systems Handbook
The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these op
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Francesco Ricci · Lior Rokach · Bracha Shapira · Paul B. Kantor Editors
Recommender Systems Handbook
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Editors Francesco Ricci Free University of Bozen-Bolzano Faculty of Computer Science Piazza Domenicani 3 39100 Bolzano Italy [email protected] Bracha Shapira Ben-Gurion University of the Negev Dept. Information Systems Engineering Beer-Sheva Israel [email protected]
Lior Rokach Ben-Gurion University of the Negev Dept. Information Systems Engineering 84105 Beer-Sheva Israel [email protected] Paul B. Kantor Rutgers University School of Communication, Information & Library Studies Huntington Street 4 08901-1071 New Brunswick New Jersey SCILS Bldg. USA [email protected]
ISBN 978-0-387-85819-7 e-ISBN 978-0-387-85820-3 DOI 10.1007/978-0-387-85820-3 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010937590 c Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Dedicated to our families in appreciation for their patience and support during the preparation of this handbook.
F.R. L.R. B.S. P.K.
Preface
Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. The suggestions provided are aimed at supporting their users in various decision-making processes, such as what items to buy, what music to listen, or what news to read. Recommender systems have proven to be valuable means for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed and during the last decade, many of them have also been successfully deployed in commercial environments. Development of recommender systems is a multi-disciplinary effort which involves experts from various fields such as Artificial intelligence, Human Computer Interaction, Information Technology, Data Mining, Statistics, Adaptive User Interfaces, Decision Support Systems, Marketing, or Consumer Behavior. Recommender Systems Handbook: A Complete Guide for Research Scientists and Practitioners aims to impose a degree of order upon this diversity by presenting a coherent and unified repository of recommender systems’ major co
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