In this paper discuss mostly the question of the structure of the quotient space theory. Comparing with rough set theory, point out the importance of the structure in granule computing theory.
主要讨论商空间理论中的结构问题，并与粗糙集方法进行比较，指出结构在粒度计算理论中的重要性。
Through defining information granule with binary string, we introduce an algorithm of mining association rules based on granular computing.
通过采用二进制串表示所定义的信息粒，提出了基于粒计算的关联规则挖掘算法。
This paper introduces the conceptions of information granules and granular computing. A relation between granule and binary numeral is established.
本文介绍了信息粒及粒计算的概念，建立了粒与二进制数的对应关系。
This paper proposes a method based on granularity computing to get the sentiment classification of text comments through rule learning by establishing the granule network.
提出了一种基于粒运算的方法，通过建立粒网络生成分类规则，从而得到评论文本的情感倾向分类。
This paper proposes a method based on granularity computing to get the sentiment classification of text comments through rule learning by establishing the granule network.
提出了一种基于粒运算的方法，通过建立粒网络生成分类规则，从而得到评论文本的情感倾向分类。
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