Community Detection in Complex Network via BGLL Algorithm
نویسندگان
چکیده
منابع مشابه
Community Detection in Complex Network via BGLL Algorithm
A large number of networks in nature, society and technology are defined by a mesoscopic level of organization, in which groups of nodes form tightly connected units, called communities, that are sparsely inter-linked to each other . Identifying this community structure is one of the most important problems in understanding of functions and structures of real world complex systems, which is sti...
متن کاملComplex Network Topology Mining and Community Detection
Recently,various heterogeneous complex networks featured as “small-world” and “scale-free” have become a common research area of different disciplines. Especially, network topology mining and community detection have become focal topics. Through the investigations of typical features in complex networks, we propose a network nodes evaluation model based on a multivariate hierarchy method. With ...
متن کاملHierarchical Agglomeration Community Detection Algorithm via Community Similarity Measures
Community detection is an important method for analyzing community structure of real-world networks. Most of the existing hierarchical agglomeration community detection algorithms have either high computational complexity or unsatisfied community detection results. In this contribution, we present a new hierarchical agglomeration community detection algorithm, called Community Detection Algorit...
متن کاملA Michigan memetic algorithm for solving the community detection problem in complex network
Community structure is an important feature in complex networks which has great significant for organization of networks. The community detection is the process of partitioning the network into some communities in such a way that there exist many connections in the communities and few connections between them. In this paper a Michigan memetic algorithm; called MLAMA-Net; is proposed for solving...
متن کاملA genetic algorithm for community detection in complex networks
A new genetic algorithm for community detection in complex networks was proposed. It adopts matrix encoding that enables traditional crossover between individuals. Initial populations are generated using nodes similarity, which enhances the diversity of initial individuals while retaining an acceptable level of accuracy, and improves the efficiency of optimal solution search. Individual crossov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2012
ISSN: 0975-8887
DOI: 10.5120/7315-9916