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计算机工程 ›› 2010, Vol. 36 ›› Issue (24): 42-44. doi: 10.3969/j.issn.1000-3428.2010.24.015

• 软件技术与数据库 • 上一篇    下一篇

一种改进的增量挖掘算法

李春喜,赵 雷   

  1. (苏州大学计算机科学与技术学院,江苏 苏州 215006)
  • 出版日期:2010-12-20 发布日期:2010-12-14
  • 作者简介:李春喜(1984-),男,硕士研究生,主研方向:数据库技术,数据挖掘;赵 雷(通讯作者),副教授
  • 基金资助:

    国家自然科学基金资助项目(61073061)

Improved Incremental Mining Algorithm

LI Chun-xi, ZHAO Lei   

  1. (School of Computer Science and Technology, Soochow University, Suzhou 215006, China)
  • Online:2010-12-20 Published:2010-12-14

摘要:

Pre-FUFP算法基于次频繁项的概念有效处理了频繁模式树的更新,但当有次频繁项变成频繁项时,需要判定原数据库中哪些事务包含该数据项。为此,通过引入次频繁项对应原事务标识符的索引确定需要处理原数据库的事务,减少这一过程所消耗的时间,并用基于压缩FP-tree和矩阵技术代替原始FP-growth挖掘出频繁模式。实验证明该算法在时间效率上较Pre-FUFP有大幅度提高。

关键词: 频繁模式, 次频繁项集, 增量挖掘

Abstract:

Pre-FUFP algorithm updates the frequent pattern tree effectively based on the concept of pre-large items. But when there are pre-large items becoming frequent items, the algorithm need check which transactions in the original database contains the pre-large items. In this paper, an index table of pre-large items to their corresponding original transactions is proposed to find out the transactions need to be processed and fasten the process of FUFP-tree modification. The frequent patterns by using compact FP-Tree and matrix based algorithm are worked out. Experimental result shows the algorithm outperforms the pre-FUFP algorithm.

Key words: frequent pattern, pre-large itemsets, incremental mining

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