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Please use this identifier to cite or link to this item: http://purl.org/purl/4107

Title: Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience
Authors: Sumam, Mary Idicula
Geethu, Miriam Jacob
Keywords: spatio-temporal data
flock patterns
clustering
frequent pattern mining
Issue Date: 2012
Publisher: IEEE
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
Description: 2012 International Conference on Data Science & Engineering (ICDSE)
URI: http://dyuthi.cusat.ac.in/purl/4107
Appears in Collections:Dr. Sumam Mary Idicula

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