Proceedings Article10.1109/FSKD.2016.7603422
An efficient and fast influence maximization algorithm based on community detection
Esmaeil Bagheri,Gholamhossein Dastghaibyfard,Ali Hamzeh +2 more
- 01 Aug 2016
pp 1636-1641
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TL;DR: An efficient and fast algorithm called ComPath+ is proposed for influence maximization based on community detection that enhances ComPath algorithm investigate the small number of nodes and preserve quality of seeds.
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Abstract: Influence maximization specifies a set of nodes that maximizes the influences in social networks. The influence maximization problem due to its importance in targeted marketing has been explored by many researchers. All proposed algorithms are not scalable and are too time consuming for large-scale social network. In this paper, an efficient and fast algorithm called ComPath+ is proposed for influence maximization based on community detection. ComPath+ enhances ComPath algorithm investigate the small number of nodes and preserve quality of seeds. The results show that proposed algorithm is more efficient and much faster than current algorithms.
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Citations
Identifying influential nodes in social networks via community structure and influence distribution difference
TL;DR: Experimental results demonstrate the superiority of the proposed influence maximization method compared with existing methods, from which one can further find that one can achieve a good tradeoff between the influence spread and the running time.
47
Diffusion Algorithms in Multimedia Social Networks: a preliminary model
Flora Amato,Vincenzo Moscato,Antonio Picariello,Giancarlo Sperlì +3 more
- 31 Jul 2017
TL;DR: A novel OSN data model is described 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.
39
Community-based Influence Maximization framework for Social Networks
Tshering Wangchuk
- 01 Jan 2018
TL;DR: In this paper, the influence maximization in social networks has a considerable role to play in the phenomenon of viral marketing, targeted advertisements and in promoting any campaigns, however, the Influence Max...
3
Multimedia social networks
Giancarlo Sperlì
- 10 Dec 2017
TL;DR: A novel data model for Multimedia Social Networks (MSNs), i.e. social networks that combine information on users -- belonging to one or more social communities -- with the multimedia content that is generated and used within the related environments is defined.
2
Diffusion Algorithms in Multimedia Social Networks: A Novel Model
Flora Amato,Vincenzo Moscato,Antonio Picariello,Giancarlo Sperlì +3 more
- 28 Aug 2018
TL;DR: This paper describes a multimedia data model for OSN in order to provide, in a unique framework, novel mechanisms for effective management of multimedia information supporting several classic applications, such as influence analysis and maximization.
2
References
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TL;DR: A new framework to tackle the influence maximization problem with an emphasis on the time efficiency issue, and shows that the proposed CIM algorithm significantly outperforms the state-of-the-art algorithms in terms of efficiency and scalability, with almost no compromise of effectiveness.
182
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