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关联规则数据挖掘方法的研究 被引量:27

Research on Method of Association Rules Data Mining
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摘要 首先简要地介绍数据挖掘和关联规则的概念、关联规则的基本原理及种类。然后详细地介绍了关联规则挖掘研究现状,讨论了Apriori算法的基本原理,同时也指出了Apriori算法的一些不足。针对这些不足提出了解决方法,描述了几种改进算法。最后对关联规则挖掘下一步的研究方向进行了展望。 This paper firstly introduces the concepts of data mining and association rules and the basic principle and kind of association rules simply. Then, research statuses of mining association roles are introduced in detail.. The basic principle of Apriori algorithm is discussed . Some deficiencies of Apriori algorithm are also presented. It proppses solution methods for these deficiencies, several improved algorithms for Apriori algorithm are described. Finally, research directions of mining association rules in the future are expected.
作者 曾孝文
出处 《计算机与现代化》 2006年第9期90-92,96,共4页 Computer and Modernization
关键词 关联规则 数据挖掘 APFIORI算法 改进算法 association rules data mining Apriori algorithm improved algorithm
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  • 1Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases [C]. Proceedings of the ACM SIGMOD conference on management of data, 1993, 207-216.
  • 2Han J, Pei J, Yin Y. Mining frequent pattems without candidate generation [C]. Proc 2000 ACM-SIGMOD Int Conf Management of Data(SIGMOD' 00), Dalas, TX, 2000.
  • 3Savasere A, Omiecinski E, Navathe S. An efficient algorithm for mining association rules in large databases[C]. Proceedings of the 21st International Conference on Very large Database,1995.
  • 4Mannila H, Toivonen H, Verkamo A. Efficient algorithm for discovering association rules[C]. AAAI Workshop on Knowledge Discovery in Databases, 1994.181-192.
  • 5Toivonen H. Sampling large databases for association rules[C].Bombay, India: Proceedings of the 22nd International Conference on Very Large Database, 1996.
  • 6Brin S, Motwani R, Silverstein C. Beyond market baskets: Generlizing association rules to correlations[C]. Proceedings of the ACM SIGMOD, 1996. 255-276.
  • 7Park J S, Chen M S, Yu P S. An effective hash-based algorithm for mining association rules[C]. San Jose, CA:Proceedings of ACM SIGMOD International Conference on Management of Data, 1995. 175-186.
  • 8Ng R, Lakshmanan L V S, Han J. Exploratory mining and pruning optimizations of constrained associations rules[C]. Seattle,Washington: Proceedings ofACM SIGMOD International Conference on Management of Data, 1998.13-24.
  • 9HANJia-wei KAMBERM.数据挖掘概念与技术[M].北京:机械工业出版社,2001.1 51-161.
  • 10冯玉才,冯剑琳.关联规则的增量式更新算法[J].软件学报,1998,9(4):301-306. 被引量:227

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