With the further research on physical meaning and digital features of the community structure in complex networks in recent years, the improvement of effectiveness and efficiency of the community mining algorithms in complex networks has become an important subject in this area. This paper puts forward a concept of the microcommunity and gets final mining results of communities through fusing different microcommunities. This paper starts with the basic definition of the network community and applies Expansion to the microcommunity clustering which provides prerequisites for the microcommunity fusion. The proposed algorithm is more efficient and has higher solution quality compared with other similar algorithms through the analysis of test r...
Community structure, one of the most popular properties in complex networks, has long been a corners...
In this paper, we propose a well targeted algorithm (GAS algorithm) for detecting communities in hig...
Network community division is the basis of concept cognition and pattern learning from social networ...
International audienceDue to the development and popularization of Internet, there is more and more ...
Abstract—Community division is an important research topic in complex network area. In order to quic...
With the explosive development of big data, information data mining technology has also been develop...
AbstractThis work proposes a method for data clustering based on complex networks theory. A data set...
Detecting communities in real world networks is an important problem for data analysis in science an...
This work proposes a method for data clustering based on complex networks theory. A data set is repr...
International audienceReal world complex networks may contain hidden structures called communities o...
In order to discover the structure of local community more effectively, this paper puts forward a ne...
In real world many complex systems can be naturally represented as complex networks of which one dis...
In order to improve the efficiency of community mining algorithm and the accuracy of community class...
Graph clustering, or community detection, is the task of identifying groups of closely related objec...
ABSTRACT. In this paper, we present a general purpose network clustering algorithm based on a novel ...
Community structure, one of the most popular properties in complex networks, has long been a corners...
In this paper, we propose a well targeted algorithm (GAS algorithm) for detecting communities in hig...
Network community division is the basis of concept cognition and pattern learning from social networ...
International audienceDue to the development and popularization of Internet, there is more and more ...
Abstract—Community division is an important research topic in complex network area. In order to quic...
With the explosive development of big data, information data mining technology has also been develop...
AbstractThis work proposes a method for data clustering based on complex networks theory. A data set...
Detecting communities in real world networks is an important problem for data analysis in science an...
This work proposes a method for data clustering based on complex networks theory. A data set is repr...
International audienceReal world complex networks may contain hidden structures called communities o...
In order to discover the structure of local community more effectively, this paper puts forward a ne...
In real world many complex systems can be naturally represented as complex networks of which one dis...
In order to improve the efficiency of community mining algorithm and the accuracy of community class...
Graph clustering, or community detection, is the task of identifying groups of closely related objec...
ABSTRACT. In this paper, we present a general purpose network clustering algorithm based on a novel ...
Community structure, one of the most popular properties in complex networks, has long been a corners...
In this paper, we propose a well targeted algorithm (GAS algorithm) for detecting communities in hig...
Network community division is the basis of concept cognition and pattern learning from social networ...