Abstract
Efficient association rule mining algorithms already exist, but as the size of databases increases, the number of patterns mined by the algorithms increases to such extent that their manual evaluation becomes impractical. An empirical evaluation is conducted using several databases, to discover whether the ranking performed by the various criteria is similar or easily distinguishable. It reveals that most of the rules found by the comparably strict parameters ranked highly according to the interestingness criteria when using lax parameters.
| Original language | English |
|---|---|
| Pages (from-to) | 63-74 |
| Number of pages | 12 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 3695 |
| State | Published - 1999 |
| Event | Proceedings of the 1999 Data Mining and Knowledge Discovery: Theory, Tools, and Technology - Orlando, FL, USA Duration: 5 Apr 1999 → 6 Apr 1999 |