Name
Abstract | ||
|---|---|---|
Data mining applications over on-body sensor data have earned great attention in recent years. We propose a novel Online Multi-divisive Hierarchical Clustering Method on on-body sensor data. Our method evolves tree-like top down hierarchy cluster, which splits and agglomerates clusters as needed. Experimental results prove a competing quality for our method over existing ones. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-1-4419-5913-3_10 | ADVANCES IN COMPUTATIONAL BIOLOGY |
Keywords | Field | DocType |
Agglomeration,Cluster accuracy,Hierarchical clustering,On-body sensor | Hierarchical clustering,Data mining,Computer science,Hierarchical clustering of networks,Consensus clustering,Cluster analysis | Conference |
Volume | ISSN | Citations |
680 | 0065-2598 | 0 |
PageRank | References | Authors |
0.34 | 2 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ibrahim Musa Ishag Musa | 1 | 0 | 1.01 |
| Gyeongmin Yi | 2 | 5 | 0.89 |
| Dong Gyu Lee | 3 | 128 | 7.62 |
| Myeong-chan Cho | 4 | 9 | 1.39 |
| Jang-Whan Bae | 5 | 114 | 3.85 |
| Keun Ho Ryu | 6 | 883 | 85.61 |
| Keun Ho Ryu | 7 | 0 | 0.34 |