ANGEL: a new effective and efficient hybrid clustering technique for large databases
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
G-TREACLE: a new grid-based and tree-alike pattern clustering technique for large databases
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
| Hi-index | 0.00 |
Many recent clustering schemes have been applied in previous investigations to resolve the issues of high execution cost and low correction ratio in arbitrary shapes. Two conventional approaches that can solve one of these problems accurately are K-means and DBSCAN. However, DBSCAN is inefficient while K-means has poor accuracy. ANGEL and G-TREACLE have been proposed to improve current clustering tribulations, but require complicated procedures and numerous thresholds. This work presents a new clustering technique, called "GOD-CS", which employs grid-based clustering, neighborhood 8-square searching and tolerance rate to reduce these problems. Simulation results indicate that GOD-CS clusters large databases very quickly, while having almost identical or even better clustering performance in comparison to several existing well-known approaches with the original patterns in a simple procedure. Thus, GOD-CS performs well and is simple to implement.