计算机工程与应用2019，Vol.55Issue(1)：35-41,7.DOI:10.3778/j.issn.1002-8331.1801-0255
基于改进k-shell算法的节点影响力的识别
Identification of Node Influence Based on Improved k-shell Algorithm
摘要
Abstract
Nodes that have greater influence in complex networks play an important role in controlling rumors propagation, optimizing resource allocation, spreading information efficiently, and advertising accurately. In view of the current many methods in identifying the node’s influence have certain limitation, this paper based on the k-shell algorithm defines the concept of weighted degree, and puts forward the Modified k-shel(l MKS)algorithm, shorted for MKS algorithm by mea-suring the potential importance of edges and considering the different contributions of neighbors. This algorithm considers the nodes’own features, location features and local features. Through implementing this algorithm on the representative Zachary karate club network and comparing with other typical methods, it is found that this algorithm improves the coarse division of k-shell algorithm, and its result is more reasonable.关键词
复杂网络/k-shell/加权度/影响力识别Key words
complex networks/k-shell/weighted degree/influence identification分类
信息技术与安全科学引用本文复制引用
朱晓霞,胡小雪..基于改进k-shell算法的节点影响力的识别[J].计算机工程与应用,2019,55(1):35-41,7.基金项目
国家自然科学基金(No.71301140) （No.71301140）
河北省自然科学基金(No.G2015203425) （No.G2015203425）
河北省三三三人才工程项目(No.A2016002038) （No.A2016002038）
河北省青年拔尖人才计划(No.BJ2017078). （No.BJ2017078）
