Referenced Items are not available for this document.
According to the efficiency bottleneck of algorithm DBSCAN, we present P-DBSCAN, a novel parallel version of this algorithm in distributed environment. By separating the database into several parts, the computer nodes carry out clustering independently; after that, the sub-results will be aggregated into one final result. P-DBSCAN achieves good results and much better efficiency than DBSCAN. Experiments show that, P-DBSCAN accelerates more than 40% on one PC, and 60% on two PCs. In addition, the parallel algorithm has much better scalability than DBSCAN, so that it can be used for clustering analysis in huge databases.
Published in:
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Date of Conference: 16-18 April 2010
- Page(s):
- 508 - 511
- E-ISBN :
- 978-1-4244-5265-1
- Print ISBN:
- 978-1-4244-5263-7
- INSPEC Accession Number:
- 11361140
- Conference Location :
- Chengdu
- Digital Object Identifier :
- 10.1109/ICIME.2010.5477926
- Product Type:
- Conference Publications
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