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对规则取舍问题的研究 被引量：7

A Study of a Pair of Rules' Acceptant or Rejective Problem
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摘要 This paper establishes a theory architecture to accept or reject or reserve synchronously a pair of rules look like A→B and B→A by analyzing correlation and sufficiency gene, and presents its algorithms. Prara 1 reduces domain specialist workload, realiazes evaluative goal of decreasing people's limitation. Prara 2 also reduces workload of mining-evaluating algorithm. This paper establishes a theory architecture to accept or reject or reserve synchronously a pair of rules look like A→B and B→A by analyzing correlation and sufficiency gene, and presents its algorithms. Praral reduces domain specialist workload, realiazes evaluative goal of decreasing people's limitation . Prara2 also reduces workload of mining-evaluating algorithm.
作者 周颖
机构地区 北京科技大学信息工程学院
出处 《计算机科学》 CSCD 北大核心 2003年第6期126-128,共3页 Computer Science
基金 国家自然科学基金重点项目(69835001) 北京市自然科学基金(4022008)
关键词 规则取舍 KDD 知识发现 相关性度量 充分性因子 人工智能 Sufficiency gene , A pair of rules , Auto-evaluate
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
  • 相关文献

参考文献1

  • 1Han Jiawei Micheline Kamber.Data Mining:Concepts and Techniques[M].高等教育出版社,2001..

同被引文献35

  • 1Fayyad U M,Piatetsky-Shapiro G., et al.From Data Mining to Knowledge Discovery:An Overview, Advances in Knowledge discovery and Data Mining[M]. Massachusettes :AAAI/MIT press, 1996. 83-115.
  • 2周颖.数据库中知识发现(KDD)的规则新颖性研究.计算机科学,2006,33(8):285-286.
  • 3Liu Huan, Lu Hongiun, Feng Ling, et al. Efficient Search of Reliable Exception[ C]//In Proc. of PAKDD - 99, Third Pacific- Asia Conference. Beijing, China: [s. n. ], 1999:194 - 203.
  • 4Hussain F, Liu H, Suzuki E, et al. Exception rule mining a relative interestingness measure[ C]//In Proc. Fourth Conf. PAKDD- 00. London: Springer Verlag,2000:86 - 97.
  • 5Suzuji E, Shurnum M. Exceptional Knowledge Discovery in Databases bases on Information Theory[C]//In Proc. of KDD - 96. AAAI. Portland, Oregon, USA: [ s. n. ], 1996:275 - 278.
  • 6Suzuki E. Autonomous Discovery of Reliable Exception Rules [ C]//In Proc. of KDD- 97. Newport Beach, CA, USA: [ s. n. ], 1997:259 - 262.
  • 7Suzuki E, Tsunnoto S. Evaluating Hypothesis - driven exception- rule with medical data sets[C]//In proc. Fourth Conf. PAKDD- 00. Kyoto,Japan: [s. n. ] ,2000:208 - 211.
  • 8Huan Liu, Hongjun Lu, Ling Feng, Farhad Hussain. Efficient Search of Reliable Exception[ C]. In Proc. of PAKDD- 99, Third Pacific- Asia Conference, Beijing,China,1999:194-203.
  • 9Hussain F, Liu H, Suzuki E, Lo H. Exception rule mining with a relative interestingness measure[ C]. In Proc. Fourth Conf. PAKDD -00, London : Springer Verlag, 2000 : 86 - 97.
  • 10Suzuji E, Shumura M. Exceptional Knowledge Discovery in Databases bases on Information Theory[ C]. In Proc. of KDD -96. AAAI, Portland, Oregon,USA, 1996:275 -278.

引证文献7

二级引证文献3

计算机科学
2003年 第6期

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