Overlapped community detection in complex networks

Pizzuti, Clara

doi:10.1145/1569901.1570019

Cited by 62 publications

(36 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pizzuti [42] presented an indirect representation of overlapping communities, wherein the network is translated into a line graph and a partition of the latter corresponds to an overlapping partition of the former. The partition of the line graph employs locus-based adjacency representation, which will prevent the production of illegal individuals.…”

Section: A Encoding Schemamentioning

confidence: 99%

Identifying overlapping communities in networks using evolutionary method

Zhan

Guan

Chen

et al. 2016

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

Abstract-Community structure is a typical property of many real-world networks, and has become a key to understand the dynamics of the networked systems. In these networks most nodes apparently lie in a community while there often exists a few nodes straddling several communities. An ideal algorithm for community detection is preferable which can identify the overlapping communities in such networks. To represent an overlapping division we develop a encoding schema composed of two segments, the first one represents a disjoint partition and the second one represents a extension of the partition that allows of multiple memberships. We give a measure for the informativeness of a node, and present an evolutionary method for detecting the overlapping communities in a network.

show abstract

Section: A Encoding Schemamentioning

confidence: 99%

Identifying overlapping communities in networks using evolutionary method

Zhan

Guan

Chen

et al. 2016

Physica A: Statistical Mechanics and its Applications

View full text Add to dashboard Cite

show abstract

“…Many algorithms have been developed to detect overlapping communities in complex networks, such as CPM [2], CONGA [5], GA-Net+ [9], etc. Among them, CPM is the most famous and widely used.…”

Section: Related Workmentioning

confidence: 99%

“…GA-Net+ [9], proposed by Pizzuti, first adopts genetic algorithm to detect overlapping communities. It proposes a method to transfer node graph to line graph, in which nodes present edges of the node graph, while edges present adjacent relationships of edges of node graph.…”

Section: Related Workmentioning

confidence: 99%

“…The node-based overlapping community detection algorithms [1,2,3,4,5,6,7,9], classify nodes of the network directly. The link-based algorithms cluster the edges of network, and map the final link communities to node communities by simply gather nodes incident to all edges within each link communities [8].…”

Section: Introductionmentioning

confidence: 99%

“…Experiment on artificial networks shows that GaoCD work well on networks with typical overlapping structure. Experiments on real networks compare GaoCD with ABL [8] and GA-NET+ [9]. It is shown that GaoCD always achieves higher partition density D and finds denser communities.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Genetic Algorithm for Overlapping Community Detection

Cai

Shi

Dong

et al. 2011

Advanced Data Mining and Applications

View full text Add to dashboard Cite

Abstract. There is a surge of community detection on complex network analysis in recent years, since communities often play special roles in the network systems. However, many community structures are overlapping in real word. For example, a professor collaborates with researchers in different fields. In this paper, we propose a novel algorithm to discover overlapping communities. Different from conventional algorithms based on node clustering, our algorithm is based on edge clustering. Since edges usually represent unique relations among nodes, edge clustering will discover groups of edges that have the same characteristics. Thus nodes naturally belong to multiple communities. The proposed algorithm apply a novel genetic algorithm to cluster on edges. A scalable encoding schema is designed and the number of communities can be automatically determined. Experiments on both artificial networks and real networks validate the effectiveness and efficiency of the algorithm.

show abstract

Community detection in social networks

Bedi

Sharma

2016

WIREs Data Min & Knowl

237

View full text Add to dashboard Cite

The expansion of the web and emergence of a large number of social networking sites (SNS) have empowered users to easily interconnect on a shared platform. A social network can be represented by a graph consisting of a set of nodes and edges connecting these nodes. The nodes represent the individuals/entities, and the edges correspond to the interactions among them. The tendency of people with similar tastes, choices, and preferences to get associated in a social network leads to the formation of virtual clusters or communities. Detection of these communities can be beneficial for numerous applications such as finding a common research area in collaboration networks, finding a set of likeminded users for marketing and recommendations, and finding protein interaction networks in biological networks. A large number of community-detection algorithms have been proposed and applied to several domains in the literature. This paper presents a survey of the existing algorithms and approaches for the detection of communities in social networks. We also discuss some of the applications of community detection.

show abstract

Overlapped community detection in complex networks

Cited by 62 publications

References 27 publications

Identifying overlapping communities in networks using evolutionary method

Identifying overlapping communities in networks using evolutionary method

A Novel Genetic Algorithm for Overlapping Community Detection

Community detection in social networks

Contact Info

Product

Resources

About