【摘 要】
：
In this paper,we propose a balanced multi-label propagation algorithm (BMLPA) for overlapping community detection in social networks. As well as its fast speed,
【机 构】
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School of Computer and Information Technology,Department of Computer Science
【基金项目】
：
the Natural Science Foundation of Beijing of China;国家自然科学基金;the Fundamental Research Funds for the Central Universities of China
论文部分内容阅读
In this paper,we propose a balanced multi-label propagation algorithm (BMLPA) for overlapping community detection in social networks. As well as its fast speed,another important advantage of our method is good stability,which other multi-label propagation algorithms,such as COPRA,lack.In BMLPA,we propose a new update strategy,which requires that community identifiers of one vertex should have balanced belonging coefficients.The advantage of this strategy is that it allows vertices to belong to any number of communities without a global limit on the largest number of community memberships,which is needed for COPRA.Also,we propose a fast method to generate "rough cores",which can be used to initialize labels for multi-label propagation algorithms,and are able to improve the quality and stability of results.Experimental results on synthetic and real social networks show that BMLPA is very efficient and effective for uncovering overlapping communities.
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