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Computing node clustering coefficients securely
Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2019When performing any analysis task, some information may be leaked or scattered among individuals who may not willing to share their information (e.g., number of individual's friends and who they are). Secure multi-party computation (MPC) allows individuals to jointly perform any computation without revealing each individual's input.
Katchaguy Areekijseree +2 more
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Network clustering coefficient without degree-correlation biases
Physical Review E, 2005The clustering coefficient quantifies how well connected are the neighbors of a vertex in a graph. In real networks it decreases with the vertex degree, which has been taken as a signature of the network hierarchical structure. Here we show that this signature of hierarchical structure is a consequence of degree-correlation biases in the clustering ...
Sara Nadiv, Soffer, Alexei, Vázquez
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Homology Detection Using Multilayer Maximum Clustering Coefficient
Journal of Computational Biology, 2018Homologous sequences are widely used to understand the functions of certain genes or proteins. However, there is no consensus to solve the automatic assignment of functions to protein problem and many algorithms have different ways of identifying homologous clusters in a given set of sequences.
Caio, Santiago +2 more
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Similar Coefficient of Cluster for Discrete Elements
Sankhya B, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
VoVan, Tai, Nguyen Trang, Thao
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An Improved Clustering Algorithm Based on Cluster Weight Coefficient
2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS), 2019Clustering algorithms are typical unsupervised machine learning algorithms, which are widely used in many fields. As a popular clustering algorithm, K-means has a good performance, but it has difficulties in determining initial clustering centers and the number of clusters.
Qiaoling Wang +3 more
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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 +4 more
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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 +4 more
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Robustness of clustering coefficients
Communications in Statistics - Theory and Methods, 2023Xiaofeng Zhao, Mingao Yuan
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A Self-learning Clustering Algorithm Based on Clustering Coefficient
2014This 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 +3 more
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High Clustering Coefficient of Computer Networks
2009 WASE International Conference on Information Engineering, 2009Due to the rapid development of network technology, the structure of computer network is increasingly complicated.The traditional random network model is difficult to haracterize the topology of current computer network.Complex network theory provides new view and thinking tostudy in this field.
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