Volume & Issue no: Volume 4, Issue 1, January - February 2015
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Title: |
Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys
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Author Name: |
Rohit K. Chandran, Ms. S. S. Pawar |
Abstract: |
Abstract
It is becoming apparent that the next generation astronomical
analysis requires good domain knowledge to handle vast
amount of astronomical data over network. The data
availability over internet has increased tremendously and
there exist a bridging gap between Computer Scientists and
Astronomers. Most of the conventional methods are directly
applied to the data without any simplification mechanism. The
K-means is a clustering algorithm that has been used widely
to classify dataset in astronomical databases. In this paper we
propose an approach to group Quasar candidates with
redshirts varying between 0.8 and 2.2 from SDSS catalogue.
Most of these Quasars lie within a single region in a color
versus red shift plot. For clustering, A similarity matrix is
generated based on its photometric properties using their nonstellar
colors ugriz photometry from SDSS Dataset. Clustering
is performed on this matrix along with red shift. This matrix
derived consists of score based on structured scientific
information that leads to find interdependencies within the
astronomical domain. The matrix eases the process of
clustering by reducing number of attributes within each
instance. The improvement in clustering performance can be
understood when the inputs are of large scale.
Keywords: Data Mining, Astro-informatics, Clustering,
Similarity evaluation, Fibonacci Series. |
Cite this article: |
Rohit K. Chandran, Ms. S. S. Pawar , "
Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys
" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 4, Issue 1, January - February 2015 , pp.
226-230 , ISSN 2278-6856.
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