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Enterprise service user intent prediction based on fast K-means++ fusion algorithm. [PDF]

PLoS One
Han Y, Zhai J, Li P.
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Mechanical Behavior and Damage Mode Identification of Wind Turbine Blade GFRP Shear Webs Based on Acoustic Emission Detection Technology. [PDF]

Sensors (Basel)
Xu L, Zheng J, Wang W, Li Z, Zou H.
europepmc   +1 more source

Overcoming missing data in spatial metabolomics with machine learning imputation to accelerate downstream discovery. [PDF]

iScience
Feng T, Wang Y, Pei S, Wang Q, Li Y, Lv J, Xia T, Chen D, Piao HL.   +8 more
europepmc   +1 more source

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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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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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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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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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