Results 271 to 280 of about 239,550 (307)

Similar Coefficient of Cluster for Discrete Elements

Sankhya B, 2018
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VoVan, Tai, Nguyen Trang, Thao
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A clustering coefficient for complete weighted networks

Network Science, 2015
AbstractThe clustering coefficient is typically used as a measure of the prevalence of node clusters in a network. Various definitions for this measure have been proposed for the cases of networks having weighted edges which may or not be directed. However, these techniques consistently assume that only a subset of all possible edges is present in the ...
Bijma, F., Mc Assey, M.P.
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From Water Clustering to Osmotic Coefficients

The Journal of Physical Chemistry A, 2010
Water 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, Bilde, Merete, Nielsen, Ole Faurskov   +2 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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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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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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Computing node clustering coefficients securely

Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2019
When 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, Yuzhe Richard Tang, Sucheta Soundarajan   +2 more
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Approximate Triangle Count and Clustering Coefficient

Proceedings of the 2018 International Conference on Management of Data, 2018
Two important metrics used to characterise a graph are its triangle count and clustering coefficient. In this paper, we present methods to approximate these metrics for graphs.
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Comparison of Similarity Coefficients for Clustering and Compound Selection

Journal of Chemical Information and Modeling, 2008
Recent studies into the use of a selection of similarity coefficients, when applied to searches of chemical databases represented by binary fingerprints, have shown considerable variation in their retrieval performance and in the sets of compounds being retrieved. The main factor influencing performance is the density distribution of the bitstrings for
Maciej Haranczyk, John D. Holliday
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Clustering Coefficients of Random Intersection Graphs

2012
Two general random intersection graph models (active and passive) were introduced by Godehardt and Jaworski (Exploratory Data Analysis in Empirical Research, Springer, Berlin, Heidelberg, New York, pp.68–81, 2002). Recently the models have been shown to have wide real life applications. The two most important ones are: non-metric data analysis and real
Erhard Godehardt, Jerzy Jaworski, Katarzyna Rybarczyk   +2 more
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