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Open AccessArticle

A Hypergraph Data Model for Expert-Finding in Multimedia Social Networks

1
Information Technology and Electrical Engineering Department (DIETI), University of Naples “Federico” via Claudio 21, 80125 Naples, Italy
2
CINI - ITEM National Lab - via Cinzia, Complesso Universitario Montesantangelo, 80125 Napoli, Italy
*
Author to whom correspondence should be addressed.
Information 2019, 10(6), 183; https://doi.org/10.3390/info10060183
Received: 28 February 2019 / Revised: 18 May 2019 / Accepted: 18 May 2019 / Published: 28 May 2019
(This article belongs to the Special Issue Social Networks and Recommender Systems)
Online Social Networks (OSNs) have found widespread applications in every area of our life. A large number of people have signed up to OSN for different purposes, including to meet old friends, to choose a given company, to identify expert users about a given topic, producing a large number of social connections. These aspects have led to the birth of a new generation of OSNs, called Multimedia Social Networks (MSNs), in which user-generated content plays a key role to enable interactions among users. In this work, we propose a novel expert-finding technique exploiting a hypergraph-based data model for MSNs. In particular, some user-ranking measures, obtained considering only particular useful hyperpaths, have been profitably used to evaluate the related expertness degree with respect to a given social topic. Several experiments on Last.FM have been performed to evaluate the proposed approach’s effectiveness, encouraging future work in this direction for supporting several applications such as multimedia recommendation, influence analysis, and so on. View Full-Text
Keywords: multimedia social networks; social network analysis; expert-finding; hypergraphs multimedia social networks; social network analysis; expert-finding; hypergraphs
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Amato, F.; Cozzolino, G.; Sperlì, G. A Hypergraph Data Model for Expert-Finding in Multimedia Social Networks. Information 2019, 10, 183.

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