| 多概念层次上基于赋范划分距离的分类算法 |
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| 引用本文： | 许骏,柳泉波. 多概念层次上基于赋范划分距离的分类算法[J]. 计算机工程, 2001, 27(7): 67-68,117 |
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| 作者姓名： | 许骏 柳泉波 |
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| 作者单位： | 北京师范大学现代教育技术研究所, |
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| 摘 要： | 应用知识发现理论与方法从大型考生信息数据库中提取隐含的、前所未知的、对决策有潜在价值的知识和规则，是当前计算机教育应用的新课题。根据网上远程考试与评价系统的特点，讨论了挖掘的目标规则类型及其挖掘算法。针对ID3算法的不足，提出了一种新的分类算法－多概念层次上基于赋范划分距离的分类算法，简要介绍了XML在知识发现过程中的应用。
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| 关 键 词： | 知识发现 数据挖掘 赋范划分距离 分类算法 数据库 远程考试系统 Internet |
| 文章编号： | 1000-3428(2001)07-0067-02 |
Classify Algorithm Based on Normal Partition Distance at Multiple Concept Levels |
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| XU Jun,LIU Quanbo. Classify Algorithm Based on Normal Partition Distance at Multiple Concept Levels[J]. Computer Engineering, 2001, 27(7): 67-68,117 |
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| Authors: | XU Jun LIU Quanbo |
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| Abstract: | Application of KDD technology to extract implicit,previously unknown,and potentially useful rules from very large databases withexaminees' information is a new task in the computer eductional application category.Based on the characteristics of distance test and evaluation system,we first discuss the result rules' kinds and relative mining algorithms.Then a new classify algorithm based on normal partition distance at multiple concept levels is addressed to overcome ID3's shortcoming.Finally application of XML in the complete process of KDD is briefly introduced. |
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| Keywords: | KDD Data mining XML Induction learning Normal partition distance Classify algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
