Abstract
Based on our years-of-research, a data mining system, DB-Miner, has been developed for interactive mining of multiple-level knowledge in large relational databases. The system implements a wide spectrum of data mining functions, including generalization, characterization, association, classification, and prediction. By incorporation of several interesting data mining techniques, including attribute-oriented induction, progressive deepening for mining multiple-level rules, and meta-rule guided knowledge mining, the system provides a user-friendly, interactive data mining environment with good performance.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 550 |
| Number of pages | 1 |
| Journal | SIGMOD Record (ACM Special Interest Group on Management of Data) |
| Volume | 25 |
| Issue number | 2 |
| DOIs | |
| State | Published - 1996 |
| Externally published | Yes |
| Event | Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data - Montreal, Can Duration: Jun 4 1996 → Jun 6 1996 |
ASJC Scopus subject areas
- Software
- Information Systems