[1]ZHENG Cunfang,HONG Wenxue,LI Shaoxiong,et al.A novel knowledge discovery visualization method based on data partial ordered structure[J].CAAI Transactions on Intelligent Systems,2016,11(4):475-480.[doi:10.11992/tis.201606019]
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A novel knowledge discovery visualization method based on data partial ordered structure

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 4 Page number: 475-480 Column: 学术论文—知识工程 Public date: 2016-07-25
Title:
A novel knowledge discovery visualization method based on data partial ordered structure
Author(s):
ZHENG Cunfang1; 2;  HONG Wenxue1;  LI Shaoxiong1;  REN Yunli1; 3
1. School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;
2. Liren College, Yanshan University, Qinhuangdao 066004, China;
3. College of Mathematics and Information Technology, Hebei Normal University of Science and Technology, Qinhuangdao 066004, China
Keywords:
decision diagram of attribute partial ordered structure; partial ordered structure; formal concept analysis; visualization; knowledge discovery
CLC:
TP182
DOI:
10.11992/tis.201606019
Abstract:
In this paper, the formal concept is first analyzed and partial order structure theory introduced. The decision diagram of attribute partial ordered structure (DDAPOS), a visualization method of rule extraction and knowledge discovery based on cognitive principles, is then proposed. After the decision problem is transformed into a decision pattern information table, the attributes of a research object can be presented in the visualized diagram. This paper introduces the principles, generation algorithm, and application examples of DDAPOS. Experimental results show that the knowledge and rules contained in the data can be represented graphically, and the decision-making rules in the data can be found effectively through analysis of the graph branches, nodes and clusters.
References:
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