Cargando…

Recommender Systems for the Social Web

The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the  Social Web has revolutionized the architecture of participation and relationship in th...

Descripción completa

Detalles Bibliográficos
Autores principales: Pazos Arias, José J, Fernández Vilas, Ana, Díaz Redondo, Rebeca P
Lenguaje:eng
Publicado: Springer 2012
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-3-642-25694-3
http://cds.cern.ch/record/1501742
_version_ 1780927052164104192
author Pazos Arias, José J
Fernández Vilas, Ana
Díaz Redondo, Rebeca P
author_facet Pazos Arias, José J
Fernández Vilas, Ana
Díaz Redondo, Rebeca P
author_sort Pazos Arias, José J
collection CERN
description The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the  Social Web has revolutionized the architecture of participation and relationship in the Web, making it necessary to restate recommendation and reconciling it with Collaborative Tagging, as the popularization of authoring in the Web, and  Social Networking, as the translation of personal relationships to the Web. Precisely, the convergence of recommendation with the above Social Web pillars is what motivates this book, which has collected contributions from well-known experts in the academy and the industry to provide a broader view of the problems that Social Recommenders might face with.  If recommender systems have proven their key role in facilitating the user access to resources on the Web, when sharing resources has become social, it is natural for recommendation strategies in the Social Web era take into account the users’ point of view and the relationships among users to calculate their predictions. This book aims to help readers to discover and understand the interplay among legal issues such as privacy; technical aspects such as interoperability and scalability; and social aspects such as the influence of affinity, trust, reputation and likeness, when the goal is to offer recommendations that are truly useful to both the user and the provider.
id cern-1501742
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2012
publisher Springer
record_format invenio
spelling cern-15017422021-04-21T23:56:16Zdoi:10.1007/978-3-642-25694-3http://cds.cern.ch/record/1501742engPazos Arias, José JFernández Vilas, AnaDíaz Redondo, Rebeca PRecommender Systems for the Social WebEngineeringThe recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the  Social Web has revolutionized the architecture of participation and relationship in the Web, making it necessary to restate recommendation and reconciling it with Collaborative Tagging, as the popularization of authoring in the Web, and  Social Networking, as the translation of personal relationships to the Web. Precisely, the convergence of recommendation with the above Social Web pillars is what motivates this book, which has collected contributions from well-known experts in the academy and the industry to provide a broader view of the problems that Social Recommenders might face with.  If recommender systems have proven their key role in facilitating the user access to resources on the Web, when sharing resources has become social, it is natural for recommendation strategies in the Social Web era take into account the users’ point of view and the relationships among users to calculate their predictions. This book aims to help readers to discover and understand the interplay among legal issues such as privacy; technical aspects such as interoperability and scalability; and social aspects such as the influence of affinity, trust, reputation and likeness, when the goal is to offer recommendations that are truly useful to both the user and the provider.Springeroai:cds.cern.ch:15017422012
spellingShingle Engineering
Pazos Arias, José J
Fernández Vilas, Ana
Díaz Redondo, Rebeca P
Recommender Systems for the Social Web
title Recommender Systems for the Social Web
title_full Recommender Systems for the Social Web
title_fullStr Recommender Systems for the Social Web
title_full_unstemmed Recommender Systems for the Social Web
title_short Recommender Systems for the Social Web
title_sort recommender systems for the social web
topic Engineering
url https://dx.doi.org/10.1007/978-3-642-25694-3
http://cds.cern.ch/record/1501742
work_keys_str_mv AT pazosariasjosej recommendersystemsforthesocialweb
AT fernandezvilasana recommendersystemsforthesocialweb
AT diazredondorebecap recommendersystemsforthesocialweb