INFORMATION GRANULES AND APPROXIMATIONS IN INCOMPLETE INFORMATION SYSTEMS

摘要：

In this paper three types of information granular structures, called similarity classes, maximal consistent blocks, and labeled blocks, in incomplete information systems are introduced.Their properties are examined.Based on the three structures of granules, three types of rough set approximation models are derived for mining of certain and possible rules in incomplete decision tables.The relationships among the three rough set models are established.

关键词： Approximations Granules Granular computing Incomplete information systems Labeled block sets Rough sets

作者: WEI-ZHI WU XIAO-PING YANG

作者单位: School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan, Zhejiang, 316004, China

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 3740-3745

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）