Automatically assigned DDC number: 00574

Manually assigned DDC number: 006312

Number of references: 16

Title: Efficient Rule-Based Attribute-Oriented Induction for Data Mining

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Subject: David W. Cheung,H. Y. Hwang,Ada W. Fu,Jiawei Han Efficient Rule-Based Attribute-Oriented Induction for Data Mining

Description: . 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 [17]. 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. Keywords: data mining, knowledge discovery in databases, rule-based concept generalization, rule-based concept hier...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 2000-08-31

Format: ps

Identifier: http://citeseer.ist.psu.edu/328913.html

Source: http://www.cs.cuhk.hk/~adafu/Pub/JIIS00.ps

Language: en

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