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Multimedia Social Network Modeling Using Hypergraphs

Multimedia Social Network Modeling Using Hypergraphs
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Author(s): Giancarlo Sperlì (University of Naples “Federico II”, Italy), Flora Amato (University of Naples “Federico II”, Italy), Vincenzo Moscato (University of Naples “Federico II”, Italy) and Antonio Picariello (University of Naples “Federico II”, Italy)
Copyright: 2018
Pages: 25
Source title: Digital Multimedia: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-3822-6.ch032

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Abstract

In this paper the authors define a novel data model for Multimedia Social Networks (MSNs), i.e. networks that combine information on users belonging to one or more social communities together with the multimedia content that is generated and used within the related environments. The proposed model relies on the hypergraph data structure to capture and to represent in a simple way all the different kinds of relationships that are typical of social networks and multimedia sharing systems, and in particular between multimedia contents, among users and multimedia content and among users themselves. Different applications (e.g. influence analysis, multimedia recommendation) can be then built on the top of the introduce data model thanks to the introduction of proper user and multimedia ranking functions. In addition, the authors provide a strategy for hypergraph learning from social data. Some preliminary experiments concerning efficiency and effectiveness of the proposed approach for analysis of Last.fm network are reported and discussed.

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