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移动社会网络信息传播模型构建与top-k节点挖掘 被引量:1

Diffusion model and top-k nodes mining for mobile social networks
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摘要 在移动社会网络中挖掘出有影响力的top-k节点,对于移动运营商作出新产品或服务战略营销决策至关重要。针对移动社会网络的特点,提出一种充分考虑移动社会网络特点的信息传播模型以及基于该模型的top-k节点挖掘算法。实验证明,该方法能准确高效地定位移动社会网络中的活跃节点,这对于移动运营商作出营销决策起着至关重要的作用。 The top-k nodes in those network systems often play critical roles in information exchanges and spreading. Thus finding those influential carriers in mobile social networks is very useful for mobile operators to make strategy, such as sales marketing etc. This paper proposed a top-k mining algorithm based on the information diffusion model. The experiments prove that the proposed algorithm can mine influential nodes efficiently and accurately in mobile social networks.
作者 史文国 王瑜
出处 《计算机应用研究》 CSCD 北大核心 2012年第8期2830-2832,2844,共4页 Application Research of Computers
关键词 信息传播模型 移动社会网络 top-k节点挖掘算法 information diffusion model mobile social networks top-k nodes mining algorithm
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  • 1CI-IEN Wei, WANG Chi, WANG Ya-jun. Scalable influence maximiza- tion for prevalent viral marketing in large-scale social networks[ C]// Proc of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York :ACM Press,2010 : 1029-1038.
  • 2CHEN Wei ,WANG Ya-jun ,YANG Si-yu. Efficient influence maximi- zation in social networks[ C ]//Proc of the 15th ACM SIGKDD Con- ference on Knowledge Discovery and Data Mining. New York:ACM Press, 2009 : 199 - 208.
  • 3WANG Yu, CONG Gao, SONG Guo-jie, et al. Community-based greedy algorithm for mining top-k influential nodes in mobile social networks[ C ]//Proc of the 16th ACM SIGKDD Conference on Know- ledge Discovery and Data Mining. New York:ACM Press,2010:1039- 1048.
  • 4DOMINGOS P, RICHARDSON M. Mining the network value of cus- tomers[ C ]//Prec of the 7th International Conference on Knowledge Discovery and Data Mining. New York : ACM Press,2001:57- 66.
  • 5KEMPE D, KLEINBERG J, TARDOS E. Influential nodes in a diffu- sion model for social networks [ C ]//Proc of the 32nd International Conference on Automata, Languages and Programming. Berlin: Sprin- ger-Verlag,2005 : 1127 -1138.
  • 6KEMPE D, KLEINBERG J, TARDOS E. Maximizing the spread of in- fluence through a social network [ C ]//Proc of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press,2003 : 137-146.
  • 7MA Hao, YANG Hai-xuan, LYU M, et al. Mining social networks using heat diffusion processes for marketing candidates selection [ C ]//Proc of the 17th ACM Conference on Information and Knowledge Manage- ment. New York : ACM Press ,2008:233-242.
  • 8SURI R N, NARAHARI Y. Determining the top-k nodes in social net- works using the shapley value[ C]//Proc of the 7th International Con- ference on Autonomous Agents and Multiagent Systems. 2008: 1509- 1512.
  • 9NEKOVEE M, MORENO Y, B1ANCONI G, et al. Theory of rumour spreading in complex social networks [ J ]. Physica A: Statistic Me- chanics and Its Applications,2007,374( 1 ) :457-470.
  • 10LOPEZ-PINTADO D. Diffusion in complex social networks [ J ]. Games and Economic Behavior,2008,62 (2) :573-590.

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