Data mining in incomplete information systems from rough set perspective
Data mining in incomplete information systems from rough set perspective
复制标题
粗糙集视角下的不完备信息系统数据挖掘
DOI：
10.1007/978-3-7908-1840-6_12
复制
发表时间：
2000
期刊：
影响因子：
--
通讯作者：
H. Rybinski
中科院分区：
文献类型：
--
作者：
Marzena Kryszkiewicz;H. Rybinski
规则挖掘是Rough Sets应用中的一个重要方面。考虑了信息系统中的不一致性和不完整性问题。给出了在大型不完备信息系统中挖掘确定性、可能性和广义决策规则的算法。该算法是基于高效的数据挖掘技术设计的关联规则生成从大型数据库。该算法能够生成系统直接支持的规则和假设规则.从不完备系统中产生的规则与系统的任何合理扩展都不矛盾。
Mining rules is of a particular interest in Rough Sets applications. Inconsistency and incompleteness issues in the information system are considered. Algorithms, which mine in very large incomplete information systems for certain, possible and generalized decision rules are presented. The algorithms are based on efficient data mining techniques devised for association rules generation from large data bases. The algorithms are capable to generate rules both supported by the system directly andhypothetical. The rules generated from incomplete system are not contradictory with any plausible extension of the system.