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感兴趣度的研究综述 被引量：1

An Overview of Measures of Interestingness
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摘要 In KDD,there are a number of patterns and rules discovered from large database by data mining,but most of them are of no interestingness to the user. How to get those that are useful and in-teresting is crucial. Therefore it is of great value to discuss the measures of interestingness of discovered patterns. Such measures of interestingness are divided into objective measures and subjective measures.The two kinds of measures of interestingness are respectively discussed in the paper. In KDD,there are a number of patterns and rules discovered from large database by data mining,but most of them are of no interestingness to the user. How to get those that are useful and interesting is crucial. Therefore it is of great value to discuss the measures of interestingness of discovered patterns. Such measures of interestingness are divided into objective measures and subjective measures. The two kinds of measures of interestingness are respectively discussed in the paper.
作者 杨炳儒 綦艳霞
机构地区 北京科技大学信息工程学院计算机系
出处 《计算机科学》 CSCD 北大核心 2001年第10期43-45,共3页 Computer Science
基金 国家自然科学基金(69835001)
关键词 感兴趣度 知识发现 关联规则 数据挖掘 数据库 Knowledge discovery,Measures of interestingness,Objective measure,Subjective measure
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献7

  • 1周欣,沙朝锋,朱扬勇,施伯乐.兴趣度——关联规则的又一个阈值[J].计算机研究与发展,2000,37(5):627-633. 被引量：91
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二级参考文献9

  • 11，Agrawal R, Mannila H, Srikant R et al. Fast discovery of association rules. In: Fayyad M, Piatetsky-Shapiro G, Smyth P eds. Advances in Knowledge Discovery and Data Mining. Menlo Park, California: AAAI/MIT Press, 1996. 307-328
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共引文献108

同被引文献7

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计算机科学
2001年 第10期

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