Recommender Systems for Social Tagging Systems - Couverture souple

Livre 14 sur 209: SpringerBriefs in Electrical and Computer Engineering

Balby Marinho, Leandro Balby

 
9781461418931: Recommender Systems for Social Tagging Systems
Couverture souple
ISBN 10 : 1461418933 ISBN 13 : 9781461418931
Editeur : Springer, 2012

Synopsis

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 the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the 'noise' that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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 the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the 'noise' that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Springer
Date d'édition
2012
Langue
anglais
ISBN 10 
1461418933
ISBN 13 
9781461418931
Reliure
Broché
Nombre de pages
124
Coordonnées du fabricant
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Allemagne

Autres éditions populaires du même titre

9781461418955: Recommender Systems for Social Tagging Systems

Edition présentée

ISBN 10 :  146141895X ISBN 13 :  9781461418955
Editeur : Springer, 2012
Couverture souple