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
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;
Conference_Titel :
Data Science & Engineering (ICDSE), 2012 International Conference on
Conference_Location :
Cochin, Kerala
Print_ISBN :
978-1-4673-2148-8
DOI :
10.1109/ICDSE.2012.6282312