Social media systems are becoming more and more popular nowadays. In order to face the overload in the amount of users and content available in these systems, social recommender systems have been developed and are largely studied in the literature. A form of social media, known as social bookmarking system, allows to share bookmarks in a social network. A user adds as a friend or follows another user and receives updates on the bookmarks added by that user. However, no approach in the literature proposes friend recommender systems in the social bookmarking domain. In this paper, we present an analysis of the state-of-the-art on user recommendation in social environments and of the structure of a social bookmarking system, in order to derive a design and an architecture of a friend recommender system in the social bookmarking domain. This study can be useful for any future research in this area, by highlighting the aspects that characterize this domain and the features that this type of recommender system has to offer.

Design and architecture of a friend recommender system in the social bookmarking domain

MANCA, MATTEO;BORATTO, LUDOVICO;CARTA, SALVATORE MARIO
2014-01-01

Abstract

Social media systems are becoming more and more popular nowadays. In order to face the overload in the amount of users and content available in these systems, social recommender systems have been developed and are largely studied in the literature. A form of social media, known as social bookmarking system, allows to share bookmarks in a social network. A user adds as a friend or follows another user and receives updates on the bookmarks added by that user. However, no approach in the literature proposes friend recommender systems in the social bookmarking domain. In this paper, we present an analysis of the state-of-the-art on user recommendation in social environments and of the structure of a social bookmarking system, in order to derive a design and an architecture of a friend recommender system in the social bookmarking domain. This study can be useful for any future research in this area, by highlighting the aspects that characterize this domain and the features that this type of recommender system has to offer.
2014
978-098931931-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/105987
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