Extension Data Mining Knowledge Representation

被引：1

作者：

Xie Guangqiang ^{[1
]}

Li Yang ^{[1
]}

机构：

[1] Guangdong Univ Technol, Fac Comp, Guangzhou 510006, Guangdong, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON APPLIED PHYSICS AND INDUSTRIAL ENGINEERING 2012, PT A | 2012年 / 24卷

关键词：

Extension data mining; extension knowledge; knowledge representation;

D O I：

10.1016/j.phpro.2012.02.036

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper research on the representation of transformable knowledge from extension data mining. Traditional data mining technology obtain static knowledge, on the contrary, extension data mining obtain transformable knowledge, which widening the source of knowledge needed in extension strategy generating system. Transformable knowledge representation using finite automata provide us a new method of extension data mining knowledge representation. (C) 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of ICAPIE Organization Committee.

引用

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页码：240 / 246

页数：7

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