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7,973
Community detection in graphs
, 2009
"... The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of th ..."
Abstract
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Cited by 821 (1 self)
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The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices
Finding community structure in networks using the eigenvectors of matrices
, 2006
"... We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as “modularity ” over possible div ..."
Abstract
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Cited by 502 (0 self)
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We consider the problem of detecting communities or modules in networks, groups of vertices with a higher-than-average density of edges connecting them. Previous work indicates that a robust approach to this problem is the maximization of the benefit function known as “modularity ” over possible
Empirical comparison of algorithms for network community detection
- In Proc. WWW’10
, 2010
"... Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest. In practice, one typically chooses an objective function that captures the intuition of a network cluster as set of nodes with better internal connectivity ..."
Abstract
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Cited by 171 (5 self)
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Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest. In practice, one typically chooses an objective function that captures the intuition of a network cluster as set of nodes with better internal
The PASCAL Visual Object Classes (VOC) Challenge
- INTERNATIONAL JOURNAL OF COMPUTER VISION
"... ... and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection. ..."
Abstract
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Cited by 629 (20 self)
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... and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection
SURVEY ON COMMUNITY DETECTION IN SOCIAL NETWORKS
"... ABSTRACT Community detection is a growing field in the area ..."
Community Detection by Affinity Propagation
"... Abstract. Community structure in networks indicates groups of vertices within which are dense connections and between which are sparse connections. Community detection, an important topic in data mining and social network analysis, has attracted considerable research interests in recent years. Motiv ..."
Abstract
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Cited by 1 (0 self)
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Abstract. Community structure in networks indicates groups of vertices within which are dense connections and between which are sparse connections. Community detection, an important topic in data mining and social network analysis, has attracted considerable research interests in recent years
Quality functions in community detection
, 2007
"... Community structure represents the local organization of complex networks and the single most important feature to extract functional relationships between nodes. In the last years, the problem of community detection has been reformulated in terms of the optimization of a function, the Newman-Girvan ..."
Abstract
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Cited by 4 (0 self)
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Community structure represents the local organization of complex networks and the single most important feature to extract functional relationships between nodes. In the last years, the problem of community detection has been reformulated in terms of the optimization of a function, the Newman
Community Detection with Prior Knowledge
"... The problem of community detection is a challenging one because of the presence of hubs and noisy links, which tend to create highly imbalanced graph clusters. Often, these resulting clusters are not very intuitive and difficult to interpret. With the growing availability of network information, the ..."
Abstract
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The problem of community detection is a challenging one because of the presence of hubs and noisy links, which tend to create highly imbalanced graph clusters. Often, these resulting clusters are not very intuitive and difficult to interpret. With the growing availability of network information
Community Detection in Complex Networks
, 2007
"... With the rapidly grown evidence that various systems in nature and society can be modeled as complex networks, community detection in networks becomes a hot research topic in physics, sociology, computer society and etc. Although this investigation of community structures has motivated many diverse ..."
Abstract
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Cited by 1 (0 self)
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With the rapidly grown evidence that various systems in nature and society can be modeled as complex networks, community detection in networks becomes a hot research topic in physics, sociology, computer society and etc. Although this investigation of community structures has motivated many diverse
Community Detection in Social Networking
"... A social structure made of nodes (individuals or organizations) that are related to each other by various interdependencies like friendship, kinship, etc. The notion of social networks, where relationships between entities are represented as links in a graph, has attracted increasing attention in th ..."
Abstract
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networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? In this paper we will discuss various community detection algorithm and measures of community detection in any complex network.
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