The use of Online Social Networks has been rapidly increased over the last years. In particular, Social Media Networks allow people to communicate, share, comment and observe different types of multimedia content. This phenomenon produces a huge amount of data showing Big Data features, mainly due to their high change rate, large volume and intrinsic heterogeneity. In this perspective, in the last decade Recommender Systems have been introduced to support the browsing of such data collections, assisting users to find "what they really need" within this ocean of information. In this research work, we propose and describe a novel recommending system for big data applications able to provide recommendations on the base of the interactions among users and the generated multimedia contents in one or more social media networks. The proposed system relies on a "user-centered" approach. An experimental campaign, using data coming from many social media networks, has been performed in order to assess the proposed approach also showing how it can obtain very promising results.

SOS: A multimedia recommender System for Online Social networks / Amato, Flora; Moscato, Vincenzo; Picariello, Antonio; Piccialli, Francesco. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 93:(2019), pp. 914-923. [10.1016/j.future.2017.04.028]

SOS: A multimedia recommender System for Online Social networks

Flora Amato;Vincenzo Moscato;Antonio Picariello;Francesco Piccialli
2019

Abstract

The use of Online Social Networks has been rapidly increased over the last years. In particular, Social Media Networks allow people to communicate, share, comment and observe different types of multimedia content. This phenomenon produces a huge amount of data showing Big Data features, mainly due to their high change rate, large volume and intrinsic heterogeneity. In this perspective, in the last decade Recommender Systems have been introduced to support the browsing of such data collections, assisting users to find "what they really need" within this ocean of information. In this research work, we propose and describe a novel recommending system for big data applications able to provide recommendations on the base of the interactions among users and the generated multimedia contents in one or more social media networks. The proposed system relies on a "user-centered" approach. An experimental campaign, using data coming from many social media networks, has been performed in order to assess the proposed approach also showing how it can obtain very promising results.
2019
SOS: A multimedia recommender System for Online Social networks / Amato, Flora; Moscato, Vincenzo; Picariello, Antonio; Piccialli, Francesco. - In: FUTURE GENERATION COMPUTER SYSTEMS. - ISSN 0167-739X. - 93:(2019), pp. 914-923. [10.1016/j.future.2017.04.028]
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0167739X17301693-main.pdf

solo utenti autorizzati

Licenza: Accesso privato/ristretto
Dimensione 1.51 MB
Formato Adobe PDF
1.51 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/707759
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 86
  • ???jsp.display-item.citation.isi??? 35
social impact