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A comparative analysis of vibrational spectra for odorant classification. [PDF]
PLoS OneÁlvarez-García A +3 more
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Dog brain atlas generated via spatially constrained spectral clustering
Hernández-Pérez R +6 more
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Load balanced clustering coefficients
Proceedings of the first workshop on Parallel programming for analytics applications, 2014Clustering 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 +2 more
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From Water Clustering to Osmotic Coefficients
The Journal of Physical Chemistry A, 2010Water activity is an important macroscopic property of aerosol particles and droplets in the atmosphere as well as aqueous solutions in many other fields of physical chemistry. This study focuses on relating water activity, described using osmotic coefficients, to the microscopic water structure in systems of atmospheric relevance, namely, aqueous ...
Frosch , Mia +2 more
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Clustering coefficients of growing networks
Physica A: Statistical Mechanics and its Applications, 2007Abstract In this paper, we develop a general analytical method to compute clustering coefficients of growing networks. This method can be applied to any network as long as we can construct and solve the dynamic equation for the degree of any node. We also verify the accuracy of the method through simulation.
Shi, Dinghua +2 more
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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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