[1]郑存芳,洪文学,李少雄,等.数据偏序结构关系中的知识发现可视化方法[J].智能系统学报,2016,11(4):475-480.[doi:10.11992/tis.201606019]
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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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]
数据偏序结构关系中的知识发现可视化方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
11
期数:
2016年第4期
页码:
475-480
栏目:
学术论文—知识工程
出版日期:
2016-07-25
- Title:
- A novel knowledge discovery visualization method based on data partial ordered structure
- Keywords:
- decision diagram of attribute partial ordered structure; partial ordered structure; formal concept analysis; visualization; knowledge discovery
- 分类号:
- TP182
- 摘要:
- 在形式概念分析与偏序结构理论基础上，针对决策模式信息表，提出一种基于认知原理的规则提取与知识发现的可视化新方法——属性偏序决策图。该方法在将决策问题转化为决策模式信息表的基础上，通过研究对象的属性特征，将其表现在可视化图形上，介绍了属性偏序结构图的原理、生成算法及应用实例。实验表明，属性偏序结构图可以将数据中蕴含的知识和规则得以形象地表示，通过对属性偏序决策图支路、节点、簇集的分析可以有效地发现数据中蕴含的决策规则。
- 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.
- 参考文献/References:
-
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备注/Memo
收稿日期:2016-06-06。
基金项目:国家自然科学基金项目（61273019，61473339，61501397）；河北省自然科学基金重点项目（F2016203443）；燕山大学青年教师自主研究计划课题（13LGB033）.
作者简介:郑存芳,男,1979年生,讲师,博士研究生,CAAI粗糙集与软计算专委会会员、CCF会员,主要研究方向为可视化模式识别、偏序结构理论、中医工程学等。先后参与国家自然科学基金3项、河北省自然科学基金3项;洪文学,男,1953年生,教授,博士生导师,燕山大学生物医学工程研究所所长,CAAI粗糙集与软计算专委会委员,主要研究方向为大数据偏序结构理论、复杂概念网络、混合数据信息融合与模式识别和中医工程学。所带领的学术团队近年来主持省部级科研项目20余项;李少雄,男,1987年生,博士研究生,主要研究方向为偏序结构理论、可视化模式识别、中医工程学等。参与国家自然科学基金项目4项。
通讯作者:洪文学.E-mail:hongwx@ysu.edu.cn.
更新日期/Last Update:
1900-01-01