Conditional evidence theory and its application in knowledge discovery

被引：0

作者：

Tang, YC ^{[1
]}

Sun, SQ

Liu, YG

机构：

[1] Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China

[2] Zhejiang Univ, State Key Lab CAD & CG, Hangzhou 310027, Zhejiang, Peoples R China

来源：

ADVANCED WEB TECHNOLOGIES AND APPLICATIONS | 2004年 / 3007卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we develop the conditional evidence theory and apply it to knowledge discovery in database. In this theory, we assume that a priori knowledge about generic situation and evidence about situation at hand can be modelled by two independent random sets. Dempster's rule of combination is a popular method used in evidence theory, we think that this rule can be applied to knowledge revision, but isn't appropriate for knowledge updating. Based on random set theory, we develop a new bayesian updating rule in evidence theory. More importantly, we show that bayesian updating rule can be performed incrementally by using Mobius transforms.

引用

页码：500 / 505

页数：6

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