Influence Maximization on Social Graphs: A Survey

Influence Maximization (IM), which selects a set of k users (called seed set) from a social network to maximize the expected number of influenced users (called influence spread), is a key algorithmic problem in social influence analysis. Due to its immense application potential and enormous technica...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2018-10, Vol.30 (10), p.1852-1872
Hauptverfasser:	Li, Yuchen, Fan, Ju, Wang, Yanhao, Tan, Kian-Lee
Format:	Artikel
Sprache:	eng
Schlagworte:	algorithm design Algorithms Classification algorithms Computational modeling Diffusion processes Influence maximization information diffusion Information dissemination Integrated circuit modeling Maximization Social network services Social networks Stochastic processes Taxonomy
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