针对现有基于派系的重叠社区发现算法难以对移动社会化网络实施的问题,该文给出一种基于移动用户行为的回路融合社区发现算法。该算法首先通过分析移动用户行为构建移动社会化网络,利用k-EC(k-Elementary Circuitl简单回路发现算法寻找移动社会化网络的后阶回路作为社区核,并按照给定的规则对社区核进行融合,得到初步社区;然后通过计算移动用户行为的相关度将余下的离散节点加入到相应的初步社区,得到最终的社区;最后通过公开数据集和仿真数据集验证了该算法在移动社会化网络社区发现方面的可行性和有效性。
Due to the characteristics of the mobile device, it is difficult to implement the existing network discovery algorithm based on clique in mobile social network. In order to solve the problem, through analyzing the mobile user behaviors, an algorithm of community discovery algorithm based on circuit merging is proposed. Firstly, the mobile social network is constructed according to the mobile user behaviors. The method finds the k-circuit as community core by using the k-Elementary Circuits (k-EC) finding algorithm. And then the community cores that have common nodes will be merged according to some given rules. Secondly, the remainder discrete nodes are added to elementary communities according to the mobile user correlation degree. Finally, the algorithm is proved more accurate and feasible in the experiments by using the public data sets and the simulated data sets.