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New Challenges for Clustering in Large Data Base
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 74 - Number 20 |
| Year of Publication: 2013 |
| Authors: Archana Tomar, Deepshikha Patel, Nitesh Gupta |
10.5120/13023-9543
|
Archana Tomar, Deepshikha Patel, Nitesh Gupta . New Challenges for Clustering in Large Data Base. International Journal of Computer Applications. 74, 20 ( July 2013), 1-4. DOI=10.5120/13023-9543
Abstract
Cluster analysis in data mining is a main application of business. This Investigation describes to present NCDBC algorithm that extends expansion seed selection into a DBSCAN algorithm. And the DBSCAN Algorithm describes the density based clustering concept and also describes its hierarchical additional room OPTICS has been planned newly, and one of the mainly triumphant approaches to clustering. Aim of this research work is to move on the high-tech clustering; mainly density-based clustering by identifying new challenges for density based clustering and proposing inventive for these challenges. In this work the proposed procedure focuses on decrease the number of seeds points and also reduces the execution time cost of searching neighborhood data. And A hierarchical clustering procedure can be useful to these interesting subspaces in order to calculate a Latitude for north and south cities and also calculate Longitude of different cities.
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