| dc.contributor.author |
Clare, Amanda |
|
| dc.contributor.author |
Williams, Hugh E. |
|
| dc.contributor.author |
Lester, Nicholas |
|
| dc.date.accessioned |
2006-04-24T15:16:38Z |
|
| dc.date.available |
2006-04-24T15:16:38Z |
|
| dc.date.issued |
2004 |
|
| dc.identifier.citation |
Clare , A , Williams , H E & Lester , N 2004 , ' Scalable Multi-Relational Association Mining ' . |
en |
| dc.identifier.other |
PURE: 68027 |
|
| dc.identifier.other |
dspace: 2160/127 |
|
| dc.identifier.uri |
http://hdl.handle.net/2160/127 |
|
| dc.description |
Clare, A., Williams, H. E. and Lester, N. M. (2004) Scalable Multi-Relational Association Mining. In proceedings of the 4th International Conference on Data Mining ICDM '04. |
en |
| dc.description.abstract |
We propose the new RADAR technique for multi-relational data mining. This permits the mining of very large collections and provides a new technique for discovering multi-relational associations. Results show that RADAR is reliable and scalable for mining a large yeast homology collection, and that it does not have the main-memory scalability constraints of the Farmer and Warmr tools. |
en |
| dc.language.iso |
eng |
|
| dc.title |
Scalable Multi-Relational Association Mining |
en |
| dc.type |
Text |
en |
| dc.type.publicationtype |
Conference paper |
en |
| dc.contributor.institution |
Department of Computer Science |
en |
| dc.contributor.institution |
Computational Biology and Bioinformatics |
en |
| dc.description.status |
Non peer reviewed |
en |