| 摘要: |
| 关联规则和时序规则是数据挖掘的任务之一.在以往的算法中,规则通常用确定的数值或概念来表示,往往不具有实际意义,而且不容易被用户理解.研究了从大型关系数据库中挖掘模糊关联规则和模糊时序规则的问题.基于模糊集合的理论,提出了两个模糊关联规则的挖掘算法,然后把它们分别扩展为模糊时序规则的挖掘算法.用模糊概念表示的规则更符合人的思维和表达习惯,增强了规则的可理解性. |
| 关键词: 模糊概念 模糊关联规则 模糊时序规则 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.69983011 (国家自然科学基金) |
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| Efficient Algorithms for Mining Fuzzy Rules in Large Relational Databases |
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CHEN Ning,CHEN An,ZHOU Long xiang
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| Abstract: |
| Mining association rules and sequential rules from large databases is an important task of data mining. Previous work is focused on definite and accurate concepts, which may not be concise and meaningful enough for human experts to easily obtain nontrivial knowledge from the rules discovered. The definition of fuzzy concepts is based on fuzzy set theory, which is especially useful when the discovered rules are presented to human experts for examination. In this paper, algorithms are presented for discovered rules are presented to guman experts for examination.In this paper,algorithms are presentrd for discovering fuzzy association rules and fuzzy sequential rules expressed by fuzzy concepts from large relational databases. |
| Key words: fuzzy concept fuzzy association rule fuzzy sequential rule |
