Despite the great amount of research done in the Online Social Networks (OSNs) field, only few works have investigated the use of multimedia data in such realm. Instead, it is the authors’ opinion that a novel data model that takes into account the intrinsic characteristics of multimedia may be of great help in managing Multimedia OSNs for providing more effective algorithms. In this paper, we describe a novel OSN data model that supports easy management of multimedia content in a unique framework, providing a more effective and efficient mechanism for data and information management in a variety of applications, especially for Influence Analysis aims.

Diffusion algorithms in multimedia social networks: A preliminary model / Amato, Flora; Moscato, Vincenzo; Picariello, Antonio; Sperli', Giancarlo. - (2017), pp. 844-851. (Intervento presentato al convegno 9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 tenutosi a Sidndey, Australia nel 31 July - 3 August, 2017) [10.1145/3110025.3116207].

Diffusion algorithms in multimedia social networks: A preliminary model

Flora Amato;Vincenzo Moscato;Antonio Picariello;Giancarlo Sperlí
2017

Abstract

Despite the great amount of research done in the Online Social Networks (OSNs) field, only few works have investigated the use of multimedia data in such realm. Instead, it is the authors’ opinion that a novel data model that takes into account the intrinsic characteristics of multimedia may be of great help in managing Multimedia OSNs for providing more effective algorithms. In this paper, we describe a novel OSN data model that supports easy management of multimedia content in a unique framework, providing a more effective and efficient mechanism for data and information management in a variety of applications, especially for Influence Analysis aims.
2017
978-145034993-2
Diffusion algorithms in multimedia social networks: A preliminary model / Amato, Flora; Moscato, Vincenzo; Picariello, Antonio; Sperli', Giancarlo. - (2017), pp. 844-851. (Intervento presentato al convegno 9th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017 tenutosi a Sidndey, Australia nel 31 July - 3 August, 2017) [10.1145/3110025.3116207].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

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/11588/708089
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 37
  • ???jsp.display-item.citation.isi??? ND
social impact