Paper Info
Title
A Similarity-Based Method for Visual Search in Time Series Using Coulomb's Law.
Abstract
We present a method for visual search in multidimensional time series based on Coulomb's law. The proposed method integrates: a descriptor based on Coulomb's law for dimensionality reduction in time series; a system to perform similarity searching in time series; and, a module for the visualization of results. Experiments were performed using real data, indicating that the proposed method broadens the quality of through similarity queries in time series.
Year
DOI
Venue
2014
10.1007/978-3-319-11988-5_22
Lecture Notes in Computer Science
Keywords
Field
DocType
Time series analysis,Index method,Similarity Search,Coulomb's law
Coulomb,Time series,Visual search,Dimensionality reduction,Computer science,Visualization,Algorithm,Artificial intelligence,Coulomb's law,Nearest neighbor search,Machine learning
Conference
Volume
ISSN
Citations 
8821
0302-9743
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Claudinei Garcia de Andrade100.34
M. X. Ribeiro26812.72