Incorporating Diversity into Influential Node Mining

Yu Zhang
Yu Zhang
Frank F. Xu
Frank F. Xu
Tianshu Lyu
Tianshu Lyu

arXiv: Artificial Intelligence, Volume abs/1810.05959, 2018.

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Abstract:

Diversity is a crucial criterion in many ranking and mining tasks. In this paper, we study how to incorporate node diversity into influence maximization (IM). We consider diversity as a reverse measure of the average similarity between selected nodes, which can be specified using node embedding or community detection results. Our goal is ...More

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