期刊文献+

并行FP-Growth算法相关技术研究

Research on the Technologies of Parallel FP-Growth Algorithm
下载PDF
导出
摘要 传统的FP-Growth算法在挖掘关联规则时,存在生成的频繁模式树可能无法实际调入内存运行和处理过程串行执行的缺点。该文研究基于FP-Growth算法的关联规则挖掘并行算法,为挖掘大型数据库中的关联规则提供了参考。 Traditional FP-Growth algorithm has the shortcomings of probabUy failing to put FP-tree into memory for actually operating and the serial processing. This paper researches the parallel algorithms based on FP-Growth algorithm, and it is a good reference for mining association rules in large databases.
作者 郝志斌 HAO Zhi-bin (School of Electronics and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China)
出处 《电脑知识与技术》 2011年第4期2220-2221,2225,共3页 Computer Knowledge and Technology
关键词 数据挖掘 关联规则 FP-GROWTH算法 并行算法 datamining association rule FP-Growth algorithm parallel algorithm
  • 相关文献

参考文献3

二级参考文献13

  • 1谈克林,孙志挥.一种FP树的并行挖掘算法[J].计算机工程与应用,2006,42(13):155-157. 被引量:10
  • 2Agrawal R, Imielinski T, Swami A N. Mining Association Rules Between Sets of Items in Large Databases[C]//Proc. of the ACM SIGMOD International Conference on Management of Data. Washington D.C., USA: ACM Press, 1993: 207-216.
  • 3Han Jiawei, Pei Jian, Yin Yiwen. Mining Frequent Patterns Without Candidate Generation[C]//Proc. of ACM-SIGMOD International Conference on Management of Data. Dallas, USA: ACM Press, 2000: 1-12.
  • 4ZaIane O R, Mohammad E H, Lu P. Fast Parallel Association Rule Mining Without Candidacy Generation[C]//Proc. of the 1st 1EEE International Conference on Data Mining. San Jose, USA: IEEE Computer Society Press, 2001: 665-668.
  • 5Liu Li, Li E, Zhang Yimin, et al. Optimization of Frequent Itemset Mining on Multiple-core Processor[C]//Proc. of the 33rd International Conference on Very Large Data Bases. Vienna, Austria: VLDB Endowment, 2007:1275-1285.
  • 6Agrawal R,Imielinski T,Swami A.Mining association rules between sets of items in large databases[C]//Proceedings of the ACM SIG- MOD International Conference Management of Date,Washington,1993:207-216.
  • 7Ha n J,Kamber M.Data mining:Concepts and techniques[M].Beijing: High Education Press, 2001.
  • 8Agrawal R,Imielinski T,Swami A.Mining association rules between sets of items in large databases[C]//Proc 1993 ACM-SIGMOD Int Conf Management of Data, Washington, DC, May 1993 : 207-216.
  • 9Savasere A,Omiecinski E,Navathe S.An efficient algorithm for mining association rules in large databases[C]//Proc of the 21st VLDB Conference, Zurich, Switzerland, 1995 : 432-443.
  • 10Agrawal R C,Agarwal C,Prasad V V V.A tree projection algorithm for generation of frequent itemscts[J].Journal of Parallel and Distributed Computing:Special Issue on High Performance Data Mining, 2000.

共引文献16

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部