Rule-Based Attribute-Oriented Induction for Knowledge Discovery

KSE '10 Proceedings of the 2010 Second International Conference on Knowledge and Systems Engineering(2010)

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摘要
This paper introduces a rule-based Attribute-Oriented (AO) Induction method on rule-based concept hierarchies that can be constructed from generalization rules. Based on analyzing some major previous approaches such as rule-based AO induction with backtracking, path-id based AO induction and a cyclic graph based AO induction, we propose a new approach to facilitate induction on the rule based case that can avoid a problem of anomaly and overcome disadvantages of these above methods. Experimental studies show that the new approach is efficient and suitable for providing condensed and qualified summarizations.
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关键词
knowledge discovery,rule-based ao induction,ao induction,qualified summarization,experimental study,generalization rule,rule-based attribute-oriented induction,rule-based concept hierarchy,new approach,induction method,cyclic graph,major previous approach,data mining,knowledge engineering,information systems,graph theory,knowledge based systems,databases,dispersion,rule based
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