Author:
Duan Xiuliang,Qiu Liqing,Sun Chengai
Abstract
This paper focuses on the influence maximization problem in social networks, which aims to find some influence nodes that maximize the spread of information. Most existing achievements usually adopt a uniform propagation probability, without considering the topic information. Moreover, the classic Independent Cascade Model and its approximations have suffered from much running time. To overcome this limitation, this paper proposed a Topic based Shortest Path Set algorithm (TSPS). Additionally, a comprehensive set of experiments are conducted on large real-world networks, showing that our proposal provides more impressive results in the aspects of influence spread and running time.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science
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