DocumentCode
3108766
Title
Detection of flock movement in spatio-temporal database using clustering techniques - An experience
Author
Jacob, Geethu Miriam ; Idicula, Sumam Mary
Author_Institution
Dept. of Comput. Sci., CUSAT, Cochin, India
fYear
2012
fDate
18-20 July 2012
Firstpage
69
Lastpage
74
Abstract
In this paper, moving flock patterns are mined from spatio- temporal datasets by incorporating a clustering algorithm. A flock is defined as the set of data that move together for a certain continuous amount of time. Finding out moving flock patterns using clustering algorithms is a potential method to find out frequent patterns of movement in large trajectory datasets. In this approach, SPatial clusteRing algoRithm thrOugh sWarm intelligence (SPARROW) is the clustering algorithm used. The advantage of using SPARROW algorithm is that it can effectively discover clusters of widely varying sizes and shapes from large databases. Variations of the proposed method are addressed and also the experimental results show that the problem of scalability and duplicate pattern formation is addressed. This method also reduces the number of patterns produced.
Keywords
data mining; pattern clustering; temporal databases; visual databases; SPARROW algorithm; clustering techniques; duplicate pattern formation problem; flock movement detection; frequent pattern mining; moving flock pattern mining; scalability problem; spatial clustering algorithm; spatio- temporal datasets; spatio-temporal database; swarm intelligence; Clustering algorithms; Data mining; Databases; Image color analysis; Market research; Particle swarm optimization; Trajectory; clustering; flock patterns; frequent pattern mining; spatio-temporal data;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Science & Engineering (ICDSE), 2012 International Conference on
Conference_Location
Cochin, Kerala
Print_ISBN
978-1-4673-2148-8
Type
conf
DOI
10.1109/ICDSE.2012.6282312
Filename
6282312
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