DBMiner: a system for mining knowledge in large relational databases
Jiawei Han, Yongjian Fu, Wei Wang, Jenny Y. Chiang, Wan Gong, Krzysztof Koperski, Deyi Li, Yijun Lu, Amynmohamed Rajan, Nebojša Stefanović, Betty Bin Xia, Osmar R. Zai͏̈ane · 1996
A data mining system, DBMiner, 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 incorporating several interesting data mining techniques, including attributeoriented induction, statistical analysis, progressive deepening for mining multiple-level knowledge, and meta-rule guided mining, the system provides a userfriendly, interactive data mining environment with good performance. Introduction With the upsurge of research and development activities on knowledge discovery in databases (PiatetskyShapiro & Frawley 1991; Fayyad et al. 1996), a data mining system, DBMiner, has been developed based on our studies of data mining techniques, and our experience in the development of an early system prototype, DBLearn. The system integrates data mining techniques with database technologies, ...