K-DBSCAN: an efficient density-based clustering algorithm supports parallel computing.
Chao DengJinwei SongSaihua CaiRuizhi SunYinxue ShiShangbo HaoPublished in: Int. J. Simul. Process. Model. (2018)
Keyphrases
- density based clustering algorithm
- parallel computing
- density based clustering
- clustering algorithm
- massively parallel
- computing systems
- shared memory
- parallel computation
- parallel programming
- computer architecture
- processing units
- field programmable gate array
- parallel computers
- commodity hardware
- attribute values
- k means
- data mining