dc.contributor.author |
Sumam, Mary Idicula |
|
dc.contributor.author |
Geethu, Miriam Jacob |
|
dc.date.accessioned |
2014-07-18T06:04:41Z |
|
dc.date.available |
2014-07-18T06:04:41Z |
|
dc.date.issued |
2012 |
|
dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4107 |
|
dc.description |
2012 International Conference on Data Science & Engineering (ICDSE) |
en_US |
dc.description.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 |
en_US |
dc.description.sponsorship |
Cochin University of Science and Technology |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.subject |
spatio-temporal data |
en_US |
dc.subject |
flock patterns |
en_US |
dc.subject |
clustering |
en_US |
dc.subject |
frequent pattern mining |
en_US |
dc.title |
Detection of Flock Movement in Spatio-Temporal Database using Clustering Techniques - an Experience |
en_US |
dc.type |
Article |
en_US |