Results 221 to 230 of about 242,831 (264)

Load balanced clustering coefficients

Proceedings of the first workshop on Parallel programming for analytics applications, 2014
Clustering coefficients is a building block in network sciences that offers insights on how tightly bound vertices are in a network. Effective and scalable parallelization of clustering coefficients requires load balancing amongst the cores. This property is not easy to achieve since many real world networks are scale free, which leads to some vertices
Oded Green, Lluís-Miquel Munguía, David A. Bader   +2 more
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GCN with Clustering Coefficients and Attention Module

2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA), 2020
Graph convolutional networks (GCN) exploit graph connectivity through their adjacency matrix. However, the assignment of equal importance to every one-hop neighbor and incognizance of intra-neighbor connectivity restricts its performance. Graph attention networks (GAT) address the problem of treating all neighbors equally by employing a self-attention ...
Rakesh Kumar Yadav, Abhishek 0003, Sourav S, Shekhar Verma   +3 more
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Community identification based on clustering coefficient

2011 6th International ICST Conference on Communications and Networking in China (CHINACOM), 2011
Researches show that numerous complex networks have clustering effect. It is an indispensable step to identify node clusters in network, namely community, in which nodes are closely related, in many applications such as identification of ringleaders in anti-criminal and anti-terrorist network, efficient storage of data in Wireless Sensor Network (WSN).
Jinbo Bai, Hongbo Li, Yan Chu 0001
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Bias correction in clustering coefficient estimation

2017 IEEE International Conference on Big Data (Big Data), 2017
Clustering coefficient (C) is an important structural property to understand the complex structure of a graph. Calculating C is a computationally intensive task. Thereby, sampling-based methods have attracted substantial research for estimating C, and the closely related metric, the number of triangles.
Roohollah Etemadi, Jianguo Lu
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Similar Coefficient of Cluster for Discrete Elements

Sankhya B, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
VoVan, Tai, Nguyen Trang, Thao
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A Self-learning Clustering Algorithm Based on Clustering Coefficient

2014
This paper presents a novel clustering algorithm based on clustering coefficient. It includes two steps: First, k-nearest-neighbor method and correlation convergence are employed for a preliminary clustering. Then, the results are further split and merged according to intra-class and inter-class concentration degree based on clustering coefficient. The
Mingjie Zhong, Zhijun Ding, Haichun Sun, Pengwei Wang 0001   +3 more
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Clustering Coefficients in Protein Interaction Hypernetworks

Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics, 2013
Modeling protein interaction data with graphs (networks) is insufficient for some common types of experimentally generated interaction data. For example, in affinity purification experiments, one protein is pulled out of the cell along with other proteins that are bound to it.
Suzanne Renick Gallagher, Debra S. Goldberg   +1 more
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The community detection algorithm based on the node clustering coefficient and the edge clustering coefficient

Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014
Community detection in complex networks can explore the information hidden in the exterior data relationships, understand the internal structure and function of complex system, and improve the efficiency of the system. So community detection has a high practical value.
null Rui Zhang, null Lei Li, null Chongming Bao, null Lihua Zhou, null Bing Kong   +4 more
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