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Erschienen in:
2012 | OriginalPaper | Buchkapitel
A PageRank-Based Heuristic Algorithm for Influence Maximization in the Social Network
verfasst von : Zhi-Lin Luo, Wan-Dong Cai, Yong-Jun Li, Dong Peng
Erschienen in: Recent Progress in Data Engineering and Internet Technology
Verlag: Springer Berlin Heidelberg
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The influence maximization is the problem of how to find a small subset of nodes (seed nodes) that could maximize the spread of influence in social network. However,it proved to be NP-hard.We propose a new heuristic algorithm, the High-PageRank greedy algorithm(HPR_Greedy),which searches the seed nodes in a small portion containing only the high-PageRank nodes, based on the power-law influence distribution in non-uniform networks. The experimental results showed that, compared with classical algorithms, the HPR_Greedy algorithm reduced search time and achieved better scalability without losing influence.