caa a22 4500 475799429 CHVBK 20180406123733.0 cr unu---uuuuu 170329e20000901xx s 000 0 eng 10.1023/A:1008778107391 doi (NATIONALLICENCE)springer-10.1023/A:1008778107391 Efficient Rule-Based Attribute-Oriented Induction for Data Mining [Elektronische Daten] [David Cheung, H.Y. Hwang, Ada Fu, Jiawei Han] Data mining has become an important technique which has tremendous potential in many commercial and industrial applications. Attribute-oriented induction is a powerful mining technique and has been successfully implemented in the data mining system DBMiner (Han et al. Proc. 1996 Int'l Conf. on Data Mining and Knowledge Discovery (KDD'96), Portland, Oregon, 1996). However, its induction capability is limited by the unconditional concept generalization. In this paper, we extend the concept generalization to rule-based concept hierarchy, which enhances greatly its induction power. When previously proposed induction algorithm is applied to the more general rule-based case, a problem of induction anomaly occurs which impacts its efficiency. We have developed an efficient algorithm to facilitate induction on the rule-based case which can avoid the anomaly. Performance studies have shown that the algorithm is superior than a previously proposed algorithm based on backtracking. Kluwer Academic Publishers, 2000 data mining nationallicence knowledge discovery in databases nationallicence rule-based concept generalization nationallicence rule-based concept hierarchy nationallicence attribute-oriented induction nationallicence inductive learning nationallicence learning and adaptive systems nationallicence Cheung David Department of Computer Science and Information Systems, The University of Hong Kong, Hong Kong aut Hwang H.Y. Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong aut Fu Ada Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong aut Han Jiawei School of Computing Science, Simon Fraser University, Canada aut Journal of Intelligent Information Systems Kluwer Academic Publishers 15/2(2000-09-01), 175-200 0925-9902 15:2<175 2000 15 10844 https://doi.org/10.1023/A:1008778107391 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1008778107391 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cheung David Department of Computer Science and Information Systems, The University of Hong Kong, Hong Kong aut NATIONALLICENCE 700 1- Hwang H.Y. Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong aut NATIONALLICENCE 700 1- Fu Ada Department of Computer Science and Engineering, Chinese University of Hong Kong, Hong Kong aut NATIONALLICENCE 700 1- Han Jiawei School of Computing Science, Simon Fraser University, Canada aut NATIONALLICENCE 773 0- Journal of Intelligent Information Systems Kluwer Academic Publishers 15/2(2000-09-01), 175-200 0925-9902 15:2<175 2000 15 10844 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer