International audienceOverlapping community structure has attracted much interest in recent years since Palla et al. proposed the k-clique percolation algorithm for community detection and pointed out that the overlapping community structure is more reasonable to capture the topology of networks. Despite many efforts to detect overlapping communities, the overlapping community problem is still a great challenge in complex networks. Here we introduce an approach to identify overlapping community structure based on an efficient partition algorithm. In our method, communities are formed by merging peripheral clusters with cores. Therefore, communities are allowed to overlap. We show experimental studies on synthetic networks and real networks ...
Presented at the 2010 International Conference on Advances in Social Networks Analysis and Mining (A...
Network communities represent basic structures for understanding the organization of real-world netw...
International audienceCommunity detection, also known as graph clustering, has been extensively stud...
International audienceOverlapping community structure has attracted much interest in recent years si...
Abstract. Recent years have seen the development of many graph clustering algorithms, which can iden...
International audienceDiscovering the hidden community structure is a fundamental problem in network...
Community structure is the key aspect of complex network analysis and it has important practical sig...
Detecting community structure is an important methodology to study complex networks. Community detec...
Community Detection is a trivial task in Network Analysis and Data Mining. A widely accepted definit...
Community detection in complex networks is a fundamental data analysis task in various domains, and ...
In community detection, the theme of correctly identifying overlapping nodes, i.e. nodes which belon...
International audienceOverlapping community detection is a popular topic in complex networks. As com...
Abstract—One of the main organizing principles in real-world networks is that of network communities...
Abstract—With the advancement in technology, we are surrounded with huge amount of data, which need ...
One way to analyze the structure of a network is to identify its communities, groups of related node...
Presented at the 2010 International Conference on Advances in Social Networks Analysis and Mining (A...
Network communities represent basic structures for understanding the organization of real-world netw...
International audienceCommunity detection, also known as graph clustering, has been extensively stud...
International audienceOverlapping community structure has attracted much interest in recent years si...
Abstract. Recent years have seen the development of many graph clustering algorithms, which can iden...
International audienceDiscovering the hidden community structure is a fundamental problem in network...
Community structure is the key aspect of complex network analysis and it has important practical sig...
Detecting community structure is an important methodology to study complex networks. Community detec...
Community Detection is a trivial task in Network Analysis and Data Mining. A widely accepted definit...
Community detection in complex networks is a fundamental data analysis task in various domains, and ...
In community detection, the theme of correctly identifying overlapping nodes, i.e. nodes which belon...
International audienceOverlapping community detection is a popular topic in complex networks. As com...
Abstract—One of the main organizing principles in real-world networks is that of network communities...
Abstract—With the advancement in technology, we are surrounded with huge amount of data, which need ...
One way to analyze the structure of a network is to identify its communities, groups of related node...
Presented at the 2010 International Conference on Advances in Social Networks Analysis and Mining (A...
Network communities represent basic structures for understanding the organization of real-world netw...
International audienceCommunity detection, also known as graph clustering, has been extensively stud...