摘要
针对制约动态网络演化分析方法发展的社团演变模式挖掘问题,设计了基于指向性变异策略和变邻域搜索算法的静态社团检测算法与基于匹配度和社团生存周期的社团演化分析算法,并采用在时刻上运行静态社团检测算法、在时序上运行社团演化分析算法的策略,提出了一种面向动态网络的社团检测与演化分析方法。并用Zachary空手道俱乐部网络和Power网络验证了该方法的可行性和有效性。
Aiming at the mining problem for evolutionary community patterns, which restricts the development of evolution analysis methods for dynamic network, this paper designs a static community detection algorithm based on a kind of directed mutation strategy and variable neighborhood search algorithm, and a community evolution analysis algorithm based on compatibility and community lifetime. Through adopting a strategy that runs static community detection algorithm on the moment and community evolution analysis algorithm on the sequential, a new community detection and evolution analysis method for dynamic network is proposed. In the experiment, the feasibility and effectiveness of the proposed method are verified by Zachary karate club network and power network.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2018年第1期117-124,共8页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(71771216)
关键词
社团检测
社团生存周期
动态网络
演化分析
community detection
community lifetime
dynamic network
evolution analysis
