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挖掘泛化序列模式的一种有效方法 被引量：2

Efficient algorithm for mining generalized sequential patterns.
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摘要 针对有时间约束的泛化序列模式的挖掘问题 ,提出了一种有效的挖掘方法 .与已有的算法相比 ,主要通过采取两种技术来提高效率 ,一是事先找出每个数据序列支持的序列模式 ,从而去除了时间因素 ,用一个快速算法来解决匹配问题 ;二是在数据序列重复较多时采用直接求交的方法 . An efficient algorithm for mining generalized sequence patterns is presented. The algorithm employs two ways for improving the efficiency. One is to find in advance the sequential patterns supported by each data sequence, thereby the time constraints are eliminated and a fast matching algorithm can be applied. The other is to compute the intersection of sequential patterns. Finally, a mining algorithm is given based on partitioning the database.
作者 邓明荣 叶福根 史烈 潘云鹤
机构地区 浙江大学决策优化研究所 浙江大学计算机系
出处 《浙江大学学报（理学版）》 CAS CSCD 2002年第4期415-422,共8页 Journal of Zhejiang University（Science Edition）
关键词 泛化序列模式 数据挖掘 数据库 关联规则 挖掘方法 事件模式 data mining sequential pattern
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论] TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献6

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同被引文献21

  • 1朱立运,朱建秋.带时间特征的序列模式挖掘算法TESP[J].计算机工程,2004,30(10):51-53. 被引量：3
  • 2刘月波,陆阶平,刘同明.基于CTID序列模式的一种改进算法[J].微机发展,2005,15(3):20-22. 被引量：1
  • 3Rakesh A, Ramakrishnan S. Mining sequential patterns [C].Proceedings of the 11th International Conference on Data Engineering, Taibei, 1995, 3-14.
  • 4Malesh J, George K, Vipin K. A universal formulation of sequential patterns[R]. Department of Computer Science, University of Minnesota, 1999, Technical Report No. 99-021.
  • 5Jian P, Jiawei H, Behzad M et al. PrefixSpan: miningsequential pattern sefficiently by prefix-projected pattern growth[C]. Proceedings of the 17th international conference on Data Engineering, Germany, April, 2001,215-224.
  • 6Mohammed J Z. SPADE: An efficient algorithm for mining frequent sequence[C]. Proceedings of Machine Learning Journal,special issue on Unsupervised Learning . 2001, 42:31-60.
  • 7Jay A, Johannes G, Tomi Y, Jason F. Sequential pattern mining using a bitmap representation[C]. Proceedngs of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. July,2002,429-435.
  • 8Ramakrishnan S, Rakesh A. Mining sequential patterns: Generalization and perfoumance improvements[C]. Proceedings 5th International conf. Extending Database Technology, SpringerVerlag, 1996, 1057: 3-17.
  • 9Tim O, Matthew D, David J et al. A family of algorithms for finding temporal structure in data[C]. Proceedings of the 6th International Workshop on Artificial Intelligence & Statistics,Florida,USA, 1997,371-378.
  • 10Minos G, Rajeev R, Kyuseok S. SPIRIT: Sequential pattern mining with regular expression constraints[C]. Proceedings of 25th international Conference on Very Large Databases, Morgan Kaufmann, 1999,223-234.

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浙江大学学报（理学版）
2002年 第4期

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