ATTRIBUTE REDUCTION OF LARGE CRISP-REAL CONCEPT LATTICES

摘要：

In this paper, we discuss the problems of attribute reduction of large crisp-real concept lattices. We show how to remove redundant attribute from real set formal contexts without loss any of knowledge. By the proposed approach, we remove the attributes which are not essential to the structure of large crisp-real concept lattices.

关键词： Concept lattice Formal concept analysis Attribute reduction

作者: MING-WEN SHAO YA-LI GUO

作者单位: School of Information Technology Jiangxi University of Finance & Economics Nanchang, Jiangxi 330013, P.R.China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 395-400

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）