Discovering fuzzy functional dependencies as semantic knowledge in large databases

被引：0
|
作者：
Wang, X [1 ]
Chen, GQ [1 ]
机构：
[1] Tsing Hua Univ, Sch Econ & Management, Beijing 100084, Peoples R China
来源：
SHAPING BUSINESS STRATEGY IN A NETWORKED WORLD, VOLS 1 AND 2, PROCEEDINGS | 2004年
关键词：
data mining; knowledge discovery; fuzzy functional dependency; Sectional FFD; Attribute FFD;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fuzzy functional dependency (FFD) is a kind of semantic knowledge and can be discovered from a large Volume Of business data. Sectional FFD and Attribute FFD are discussed so as to reflect semantics of the business world and express useful information that is natural for people to comprehend. The experimental results on an insurance data set show that the proposed method can extract knowledge efficiently and effectively.
引用
收藏
页码：1136 / 1139
页数：4
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