Data Mining Integrated with Domain Knowledge

被引：3

作者：

Huang, Anqiang ^{[1
,2
]}

Zhang, Lingling ^{[1
,2
]}

Zhu, Zhengxiang ^{[3
]}

Shi, Yong ^{[2
]}

机构：

[1] Chinese Acad Sci, Grad Univ, Sch Management, Beijing 100190, Peoples R China

[2] CAS,, Res Ctr Fictitious Econ & Data Sci, Beijing 100190, Peoples R China

[3] Dalian Univ Technol, Inst Syst Engn, Dalian, Peoples R China

来源：

CUTTING-EDGE RESEARCH TOPICS ON MULTIPLE CRITERIA DECISION MAKING, PROCEEDINGS | 2009年 / 35卷

基金：

北京市自然科学基金; 中国国家自然科学基金;

关键词：

Domain knowledge; data mining; interestingness; actionable; ontology;

D O I：

10.1007/978-3-642-02298-2_28

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Traditional data mining is a data-driven trial-and-error process[1], which aims at discovered pattern/rule. People either view data mining as an autonomous process, or only analyze the issues in an isolated and case-by-case manner. Because it overlooks some valuable information, such as existing knowledge, expert experience, context and real constraints, the results coming out can't be directly applied to support decisions in business. This paper proposes a new methodology called Data Mining Integrated With Domain Knowledge, aiming to discovery more interesting, more actionable knowledge.

引用

页码：184 / +

页数：2