关键词: 知识发现, 近似集, 动态获取

Abstract: In real-life applications, an information system may vary with time. This paper discusses the approaches for dynamically acquiring approximations in variable precision rough set model while adding or deleting an attribute respectively in information system. By dividing original equivalent classes in information system, this paper proposes an approach which avoids the re-division of the universe and improves the efficiency of dynamically acquiring approximations. By discussing the relationship between equivalent classes and original approximations, this paper gives the corresponding theorems between updated approximations and original approximations, and proposes the approaches for dynamically acquiring approximations while adding or deleting an attribute in variable precision rough set model respectively. The experimental results verify the validity of the proposed approaches, and the efficiency of the proposed approaches is better than that of the original approaches.

Key words: knowledge discovery, approximation, dynamic acquisition