[PDF] Top 20 Community detection in networks without observing edges
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Community detection in networks without observing edges
... network edges are unobservable typically involve a complicated process that is highly sensitive to specific design decisions and parameter ...inferred, community detection is applied to uncover ... See full document
12
Community Detection in Social Networks Considering Topic Correlations
... However, several issues have not been well resolved by existing methods. By analyzing a large number of social networks, beyond the observation that a community might focus on several topics (Jin et al. ... See full document
8
Community detection in networks: a game theoretic framework
... of community structure, various community detection approaches have been proposed in the literature to identify meaningful communities in net- works ...Existing community detection ... See full document
12
Overlapping community detection for count-value networks
... overlapping community has become a very hot research topic in the ...overlapping community detection for count-value networks that naturally arise and are pervasive in our modern life, has not ... See full document
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A STUDY ON EFFICIENT COMMUNITY DETECTION TECHNIQUES IN SOCIAL NETWORKS
... A community in a social network can also be defined as a collection of users considered as a group such that there are high interrelations or associations among members within the ...social networks and ... See full document
8
SOCIAL NETWORKS COMMUNITY DETECTION USING THE SHAPLEY VALUE
... these networks has received significant ...the community detection problem (CDP) by a novel framework based on Information Diffusion Model and Shapley Value ...the community structure of the ... See full document
15
Significance-based community detection in weighted networks
... Many community detection methods are based on a null model, which in this context means a random network model without explicit community ...un-weighted networks the most common null is ... See full document
48
Research on Community Center metric and Community Detection Algorithm for Complex Networks
... local community algorithms do, the fitness function F index is proposed to measure the difference of connection density within and outside the ...of community detection are instable because of the ... See full document
6
Improved spectral community detection in large heterogeneous networks
... of networks into communities (Fortunato, ...the community memberships to continuous scores, it is shown that approximate modularity maximization and even statistical inference methods can be performed via a ... See full document
49
An Entropy Gain Ratio based Algorithm for Community Detection in Mobile Social Networks
... Complex networks have proved to be a useful tool to model structural complexity of a variety of complex systems in different domains including sociology, biology, ethology and computer ...science. Community ... See full document
6
Multi Comm_Plus: A Community Detection System for Identification of Community in Multi-Dimensional Networks
... detecting community structures in dynamic social networks. Quick Community Adaptation (QCA) [16] is an adaptive modularity based method for identifying and tracing community structure in ... See full document
6
A parallel self-organizing overlapping community detection algorithm based on swarm intelligence for large scale complex networks
... overlapping community structures discovered by the two algorithms are quite different, for example, the over- lapping memberships and overlapping vertexes detected by one algorithm are small and less, while those ... See full document
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A parallel self-organizing community detection algorithm based on swarm intelligence for large scale complex networks
... for community structure analysis, with a near-linear time ...a community structure, it will has a high prob- ability propagating within a ...the community to which it belongs, then each vertex sends ... See full document
10
The many facets of community detection in complex networks
... on community detection has primarily focused on modelling the dynamics with Markovian diffusion processes (Delvenne et ...a community corresponding to the fast time-scale, before it can escape and ... See full document
13
Community detection in networks via nonlinear modularity eigenvectors
... As community detection using modularity maximization is known to be NP-hard, different strategies have been proposed to compute an approximate ...of community detection, a nonlinear relaxation ... See full document
23
Generalized Louvain Method for Community Detection in Large Networks
... ranking edges by using the betweenness centrality as measure of importance; ii) deleting edges in order of importance, evaluating the increase of the value of ...deleting edges with high value of ... See full document
6
Influence spreading model used to analyse social networks and detect sub-communities
... community detection. A definition for modularity is the fraction of the edges that fall within the given group minus the expected fraction if edges were distributed at ... See full document
39
Using adjacency matrices to lay out larger small world networks
... same community than they are to those outside their ...community. Community detection is usually only based on the topological properties of the graph rather than on ...different ... See full document
14
Inferring animal social interaction using proximity based on BLE and LoRa
... social networks but is also used for the monitoring of the social networks of animals, animal social network ...density, community detection, component detection, betweenness and ... See full document
93
Outlier edge detection using random graph generation models and applications
... and edges that are made by scammers, malicious programs or mistakenly by normal ...and edges is important for data mining and graph ...of edges and propose effective outlier edge detection ... See full document
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