标题:Maximizing the Influence Ranking Under Limited Cost in Social Network
作者:Hong, Xiaoguang; Liu, Ziyan; Peng, Zhaohui; Chen, Zhiyong; Li, Hui
通讯作者:Peng, Zhaohui
作者机构:[Hong, Xiaoguang; Liu, Ziyan; Peng, Zhaohui; Chen, Zhiyong; Li, Hui] Shandong Univ, Sch Comp Sci & Technol, Jinan, Peoples R China.; [Chen, Zhiyong] 更多
会议名称:18th Asia-Pacific Web Conference (APWeb)
会议日期:SEP 23-25, 2016
来源:Web Technologies and Applications, Pt I
出版年:2016
卷:9931
页码:220-231
DOI:10.1007/978-3-319-45814-4_18
关键词:Social network; Influence propagation; Competition; Cost; Multi-step; influence adjust
摘要:Influence maximizing is an important problem which has been studied widely in recent years. There are many situations in which people are more concerned about influence ranking than influence coverage in competition network, because some times only the top-ranked users can win the rewards, while few researchers have studied this problem. In this paper, we consider the problem of selecting a seed set under limited cost to get as high influence ranking as possible. We show this problem is NP-hard and propose a Intelligent Greedy algorithm to approximately solve the problem and improve the efficiency based on the submodularity. Furthermore, a new Cost-Effective Multi-Step Influence Adjust algorithm is proposed to get high efficiency. Experimental results show that our Intelligent Greedy algorithm achieves better effectiveness than other algorithms and the Cost-Effective Multi-Step Influence Adjust algorithm achieves high efficiency and gets better effectiveness than Degree and Random algorithms.
收录类别:CPCI-S;EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989315186&doi=10.1007%2f978-3-319-45814-4_18&partnerID=40&md5=e187c10bc63c4b662ae1a0c75d985067
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