文章基本信息

标题：A Multi-Threshold Granulation Model for Incomplete Decision Tables
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作者：Li, Renpu ; Yu, Tao ; Zhou, Chunjie 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2014
卷号：9
期号：7
页码：1922-1929
DOI：10.4304/jsw.9.7.1922-1929
语种：English
出版社：Academy Publisher
摘要：How to establish basic granules of knowledge is a fundamental issue for data mining from incomplete decision tables. In the existing methods, basic granules under similarity relation contain too many objects and disturb the later knowledge mining, while granules under limited similarity relation, although simplifying the granules through introducing a limited threshold on two objects satisfying similarity relation, still have problems such as high computation and low prediction precision. In this paper, a multi-threshold model is presented to establish basic knowledge units of incomplete decision table based on the idea of granular computing, comparison experiments on the new model with two existing models show that the new model is superior to the other models on prediction precision, time cost and attribute reduction. extension description logic--ALC_D-ES. Syntax definition, semantic explanation and reasoning algorithm Tableau_D-ES are given in details, which lay the theoretical foundation for the automatic solving method of contradiction problem based on extension description logic reasoning.
关键词：Incomplete decision tables;similarity relation;granular computing;multi-threshold