scholarly journals GO functional similarity clustering depends on similarity measure, clustering method, and annotation completeness

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Meng Liu ◽  
Paul D. Thomas
Keyword(s):  
Similarity Measure ◽  
Functional Similarity ◽  
Clustering Method

scholarly journals A hierarchical clustering method for random intervals based on a similarity measure

2021 ◽  
Author(s):  
Ana Belén Ramos-Guajardo
Keyword(s):  
Hierarchical Clustering ◽  
Similarity Measure ◽  
Clustering Algorithm ◽  
Real Life ◽  
Stopping Criterion ◽  
Clustering Method ◽  
Bootstrap Test ◽  
Empirical Performance ◽  
Random Intervals ◽  
Expected Values

AbstractA new clustering method for random intervals that are measured in the same units over the same group of individuals is provided. It takes into account the similarity degree between the expected values of the random intervals that can be analyzed by means of a two-sample similarity bootstrap test. Thus, the expectations of each pair of random intervals are compared through that test and a p-value matrix is finally obtained. The suggested clustering algorithm considers such a matrix where each p-value can be seen at the same time as a kind of similarity between the random intervals. The algorithm is iterative and includes an objective stopping criterion that leads to statistically similar clusters that are different from each other. Some simulations to show the empirical performance of the proposal are developed and the approach is applied to two real-life situations.

A Comparative Analysis of the Direct Clustering Algorithms Based on Different Similarity Measure of Vague Sets

2013 ◽  
Vol 380-384 ◽  
pp. 1488-1494
Author(s):  
Wang Wei ◽  
Jin Yue Peng
Keyword(s):  
Similarity Measure ◽  
Clustering Analysis ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Evaluation Criteria ◽  
Experimental Result ◽  
Clustering Method ◽  
Vague Sets ◽  
Intelligence System ◽  
System Clustering

In the research and development of intelligence system, clustering analysis is a very important problem. According to the new direct clustering algorithm using similarity measure of Vague sets as evaluation criteria presented by paper, the Vague direct clustering method are used to analysis using different similarity measure of Vague sets. The experimental result shows that the direct clustering method based on the similarity of Vague sets is effective, and the direct clustering method based on different similarity measure of Vague sets is the same basically, but difference on the steps of clustering. To select different algorithms according different conditions in the work of the actual applications.

DNAc: A Clustering Method for Identifying Kinship Relations Between DNA Profiles Using a Novel Similarity Measure*

2010 ◽  
Vol 56 ◽  
pp. S17-S22 ◽  
Author(s):  
Aimé Ntwari ◽  
Abdellali Kelil ◽  
Régen Drouin ◽  
Ernest Monga ◽  
Shengrui Wang ◽  
...  
Keyword(s):  
Similarity Measure ◽  
Clustering Method ◽  
Kinship Relations ◽  
Dna Profiles

Quantitative Measures for Design by Analogy

2000 ◽  
Author(s):  
Daniel A. McAdams ◽  
Kristin L. Wood
Keyword(s):  
Similarity Measure ◽  
Quantitative Measure ◽  
Layout Design ◽  
Functional Similarity ◽  
Original Design ◽  
Design By Analogy

Abstract In this paper a quantitative measure for design-by-analogy is developed. This measure is based on the functional similarity of products. By using this product similarity measure, designers are able to formalize and quantify design-by-analogy techniques during concept and layout design. The similarity measure and its application is clarified and validated through a case study. The case study is the original design of a pickup winder.

A Power Network Partitioning Method Based on Local Similarity Measure

2012 ◽  
Vol 588-589 ◽  
pp. 364-367
Author(s):  
Tao Wang ◽  
Heng Zhou ◽  
Pan Zou
Keyword(s):  
Hierarchical Clustering ◽  
Similarity Measure ◽  
Reactive Power ◽  
Graph Model ◽  
Weighted Graph ◽  
Local Similarity ◽  
Network Partitioning ◽  
Power Network ◽  
Clustering Method ◽  
Partitioning Algorithm

A power network partitioning model based on the weighed local similarity measure is presented in this paper considering the regional decoupling characteristics of reactive power. A weighted graph model of reactive power network is established and a new measurement of local similarity based on weighed graph is defined. To utilize our measurement of similarity to partition reactive power network, a partitioning algorithm based on generalized ward hierarchical clustering method is proposed. The algorithm can ensure balance of the reactive power inside partition. Applying the proposed algorithm to IEEE 39-bus system, the results show that the proposed algorithm is feasible and effective.

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