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Parallel clustering by fast search and find of density peaks
- Source :
- 2016 International Conference on Audio, Language and Image Processing (ICALIP).
- Publication Year :
- 2016
- Publisher :
- IEEE, 2016.
-
Abstract
- The algorithm clustering by fast search and find of density peaks shows good efficiency and accuracy, but the space complexity of the algorithm is too high since it has to keep a global distance matrix in memory, so it can hardly process big dataset clustering. To solve this problem, this paper designed a new strategy for the algorithm to search the important quantity δ, by using the new strategy, the space complexity of the algorithm is greatly reduced. And based on that reduction, a corresponding load balanced parallel clustering algorithm was presented in this paper, experimental results show that the parallel algorithm is efficient and scalable.
- Subjects :
- DBSCAN
Mathematical optimization
Computer science
Correlation clustering
Parallel algorithm
02 engineering and technology
Data stream clustering
CURE data clustering algorithm
Search algorithm
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Canopy clustering algorithm
020201 artificial intelligence & image processing
Cluster analysis
Algorithm
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2016 International Conference on Audio, Language and Image Processing (ICALIP)
- Accession number :
- edsair.doi...........b8fc3cccfd700885979d5cd91265b43b