Dynamic shape retrieval by hierarchical curve matching, snakes and data mining

2002 ◽  
Author(s):  
J. You ◽  
P. Bhattacharya
Keyword(s):  
Data Mining ◽  
Shape Retrieval ◽  
Curve Matching ◽  
Dynamic Shape

GEOMETRIC APPROACH TO DATA MINING

2001 ◽  
Vol 01 (02) ◽  
pp. 363-386
Author(s):  
WLADIMIR RODRIGUEZ ◽  
MARK LAST ◽  
ABRAHAM KANDEL ◽  
HORST BUNKE
Keyword(s):  
Data Mining ◽  
Edit Distance ◽  
Geometric Approach ◽  
Symbolic Representation ◽  
Pattern Identification ◽  
Curve Matching ◽  
Distance Computation ◽  
String Edit Distance

In this paper, a new, geometric approach to pattern identification in data mining is presented. It is based on applying string edit distance computation to measuring the similarity between multi-dimensional curves. The string edit distance computation is extended to allow the possibility of using strings, where each element is a vector rather than just a symbol. We discuss an approach for representing 3D-curves using the curvature and the tension as their symbolic representation. This transformation preserves all the information contained in the original 3D-curve. We validate this approach through experiments using synthetic and digitalized data. In particular, the proposed approach is suitable to measure the similarity of 3D-curves invariant under translation, rotation, and scaling. It also can be applied for partial curve matching.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Challenges and Cloud Computing Environments Towards Big Data

2014 ◽  
pp. 203-208
Author(s):  
Kiran Kumar S V N Madupu
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Technology Development ◽  
Computing Environments ◽  
Modern Technologies

Big Data has terrific influence on scientific discoveries and also value development. This paper presents approaches in data mining and modern technologies in Big Data. Difficulties of data mining as well as data mining with big data are discussed. Some technology development of data mining as well as data mining with big data are additionally presented.

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