期刊文献+

Research and Application on Web Information Retrieval Based on Improved FP-Growth Algorithm 被引量:2

Research and Application on Web Information Retrieval Based on Improved FP-Growth Algorithm
下载PDF
导出
摘要 A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each node are kept. Route information of different nodes in a same item are compressed into aggregative chains so that the frequent patterns will be produced in aggregative chains without generating node links and conditional pattern bases. An example of Web key words retrieval is given to analyze and verify the frequent pattern algorithm in this paper. A kind of single linked lists named aggregative chain is introduced to the algorithm, thus improving the architecture of FP tree. The new FP tree is a one-way tree and only the pointers that point its parent at each node are kept. Route information of different nodes in a same item are compressed into aggregative chains so that the frequent patterns will be produced in aggregative chains without generating node links and conditional pattern bases. An example of Web key words retrieval is given to analyze and verify the frequent pattern algorithm in this paper.
出处 《Wuhan University Journal of Natural Sciences》 CAS 2006年第5期1065-1068,共4页 武汉大学学报(自然科学英文版)
基金 Supported by the Natural Science Foundation ofLiaoning Province (20042020)
关键词 data mining CHAINS FP-growth algorithm frequent pattern aggregative information retrieval data mining chains FP-growth algorithm frequent pattern aggregative information retrieval
  • 相关文献

参考文献12

  • 1杨明,孙志挥.一种基于前缀广义表的关联规则增量式更新算法[J].计算机学报,2003,26(10):1318-1325. 被引量:23
  • 2张勇,杨玲.一个不需要产生候选集频繁集挖掘算法的研究[J].吉林农业大学学报,2003,25(3):346-349. 被引量:3
  • 3Mohammed J. Zaki.Mining Non-Redundant Association Rules[J].Data Mining and Knowledge Discovery.2004(3)
  • 4Tsai C F,,Lin Y C,Chen C P.A New Fast Algorithms for Mining Association Rules in Large Databases[ C[].Proceedings of the IEEE International Conference on Systems Man and Cybernetic.2002
  • 5Han,J,Kamber,M. Data Mining: Concepts and Techniques . 2001
  • 6Agrawa L 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
  • 7Agrawa L R.Fast Algorithms for Mining Association Rules[].Proceedings of the th International Conference on Very Large Databases.1994
  • 8Aly H H,,Taha Y,Amr A A.Fast Mining of Association Rules in Large-Scale Problems[ C][].Proceedings of the th IEEE Symp on Computers and Communications.2001
  • 9Han J,,Pei J,Yin Y.Mining Frequent Patterns without Candidate Generation [ C][].Proceedings of the ACM SIGMOD Conference.2000
  • 10Pei J,,Han J,Mortazavi-Asl B, et al.Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth[].ICDE’.2001

二级参考文献4

  • 1Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases [A]. In : Bunemuu P, Jajodia S// Proceedings of the 1993 SIGMOD Conference on Management of Data[C]. New York : NY ACM Press, 1993 : 207-216.
  • 2Han Jia-wei, Pei Jian,Yin Yi-wen. Mining frequent patterns without candidate generation [A]. In:Dayal U, Gray P M D, Nishio S// Proceedings of the International Conference on Very Large Database[ C ]. San Francisco, CA : Morgan Kanfmann Press, 1999 : 420-431.
  • 3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
  • 4肖利,金远平,徐宏炳,王能斌.基于多维标度的快速挖掘关联规则算法[J].软件学报,1999,10(7):749-753. 被引量:16

共引文献22

同被引文献4

引证文献2

二级引证文献5

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