 | 2004 |
6 |  | Christian Böhm,
Florian Krebs:
The k-Nearest Neighbour Join: Turbo Charging the KDD Process.
Knowl. Inf. Syst. 6(6): 728-749 (2004) |
| 2003 |
5 |  | Christian Böhm,
Florian Krebs:
Supporting KDD Applications by the k-Nearest Neighbor Join.
DEXA 2003: 504-516 |
| 2002 |
4 |  | Christian Böhm,
Florian Krebs,
Hans-Peter Kriegel:
Optimal Dimension Order: A Generic Technique for the Similarity Join.
DaWaK 2002: 135-149 |
3 |  | Christian Böhm,
Florian Krebs:
High Performance Data Mining Using the Nearest Neighbor Join.
ICDM 2002: 43-50 |
| 2001 |
2 |  | Stefan Berchtold,
Christian Böhm,
Daniel A. Keim,
Florian Krebs,
Hans-Peter Kriegel:
On Optimizing Nearest Neighbor Queries in High-Dimensional Data Spaces.
ICDT 2001: 435-449 |
1 |  | Christian Böhm,
Bernhard Braunmüller,
Florian Krebs,
Hans-Peter Kriegel:
Epsilon Grid Order: An Algorithm for the Similarity Join on Massive High-Dimensional Data.
SIGMOD Conference 2001: 379-388 |