Φ-Rough Sets Theory and Its Usage on Mining Approximate Dependencies
| 详细信息 | 推荐本文 | |
- 作者：Yiyong Xiao ; Ikou Kaku ; Wenbing Chang
- 关键词：Rough set theory ; Database ; Functional dependency ; Approximate dependency ; Partial approximate dependency
- 刊名：Lecture Notes in Computer Science
- 出版时间：2008
- 出版年：2008
- 期刊代码：99_0302-9743
- 类别：cp
- 卷：5227
- 期：1
- 页码：922-934
- 数据来源：sp
摘要
In this paper, we present an extension of the rough set theory based on similarity relation, called Φ-Rough Set Theory, where the indiscernibility relation of the crisp rough set theory is replaced by the notion of Φ-approximate equivalence relation. Many of the related concepts of crisp rough set theory are redefined, e.g., equivalence class, lower and upper approximations, Φ-reduction, etc. After that, we give an adequate interpretation of approximate dependencies(ADs) and partial approximate dependencies(PADs) from the point of view of Φ-RST, which sheds a new light on the functional dependency(FD) theories. The methodologies of Φ-Rough Set Theory are used on mining the ADs and PADs, on relational or fuzzy relational schema database. Finally, a numeric example is given to illustrate the process of mining the ADs and PADs in decision system database with similarity relation.