Recommender Systems for Social Tagging Systems
Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find
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Leandro Balby Marinho • Andreas Hotho Robert Jäschke • Alexandros Nanopoulos Steffen Rendle • Lars Schmidt-Thieme Gerd Stumme • Panagiotis Symeonidis
Recommender Systems for Social Tagging Systems
Leandro Balby Marinho Federal University of Campina Grande Brazil [email protected]
Andreas Hotho University of Würzburg Germany
Robert Jäschke University of Kassel Germany
Alexandros Nanopoulos University of Hildesheim Germany
Steffen Rendle University of Konstanz Germany
Lars Schmidt-Thieme University of Hildesheim Germany
Gerd Stumme University of Kassel Germany
Panagiotis Symeonidis Aristotle University Greece
ISSN 2191-8112 e-ISSN 2191-8120 ISBN 978-1-4614-1893-1 e-ISBN 978-1-4614-1894-8 DOI 10.1007/978-1-4614-1894-8 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2012931154
¤ The Author(s) 2012 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)
Preface
Social tagging systems are Web 2.0 applications that promote user participation through facilitated content sharing and annotation of that content with freely chosen keywords, called tags. Despite the potential of social tagging to improve organization and sharing of content, without efficient tools for content filtering and search, users are prone to suffer from information overload as more and more users, content, and tags become available on-line. Recommender systems are among the best known techniques for helping users to filter out and discover relevant information in large datasets. However, social tagging systems put forward new challenges for recommender systems since – differently from the standard recommender setting where users are mainly interested in content – in social tagging systems users may additionally be interested in finding tags and even other users. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving social tagging systems. While by no means exhaustive, the chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in social tagging systems. The focus is on tag recommendations and tag-aware recommendations, which are the prevalent recommenda
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