文章基本信息

标题：Record Based Relational Peculiarity Oriented Mining
本地全文：下载
作者：Muneaki Ohshima ; Ning Zhong
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2007
卷号：22
期号：1
页码：1-9
DOI：10.1527/tjsai.22.1
出版社：The Japanese Society for Artificial Intelligence
摘要：Peculiarity oriented mining (POM) is different from, and complementary to, existing approaches for discovering new, surprising and interesting patterns hidden in data. A main task of mining peculiarity rules is peculiarity identification. Previous methods for finding peculiar data are attribute-based approaches. This paper extends peculiarity oriented mining to relational peculiarity oriented mining (RPOM) in which peculiar data are identified on the record level. The experimental results in image sequences of tracking multiple walking people show that the proposed RPOM approach is effective.
关键词：data mining ; relational peculiarity oriented mining