An FP-tree based approach for mining all strongly correlated item pairs

Zengyou He; Shengchun Deng; Xiaofei Xu

doi:10.1007/11596448_108

An FP-tree based approach for mining all strongly correlated item pairs

Zengyou He^*
, Shengchun Deng
, Xiaofei Xu

^*Corresponding author for this work

Faculty of Computing

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Based on the FP-tree data structure, this paper presents an efficient algorithm for mining the complete set of positive correlated item pairs. Our experimental results on both synthetic and real world datasets show that, the performance of our algorithm is significantly better than that of the previously developed Taper algorithm over practical ranges of correlation threshold specifications.

Original language	English
Title of host publication	Computational Intelligence and Security - International Conference, CIS 2005, Proceedings
Pages	735-740
Number of pages	6
DOIs	https://doi.org/10.1007/11596448_108
State	Published - 2005
Event	International Conference on Computational Intelligence and Security, CIS 2005 - Xi'an, China Duration: 15 Dec 2005 → 19 Dec 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3801 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computational Intelligence and Security, CIS 2005
Country/Territory	China
City	Xi'an
Period	15/12/05 → 19/12/05

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10.1007/11596448_108

Cite this

He, Z., Deng, S., & Xu, X. (2005). An FP-tree based approach for mining all strongly correlated item pairs. In Computational Intelligence and Security - International Conference, CIS 2005, Proceedings (pp. 735-740). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3801 LNAI). https://doi.org/10.1007/11596448_108

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title = "An FP-tree based approach for mining all strongly correlated item pairs",

abstract = "Based on the FP-tree data structure, this paper presents an efficient algorithm for mining the complete set of positive correlated item pairs. Our experimental results on both synthetic and real world datasets show that, the performance of our algorithm is significantly better than that of the previously developed Taper algorithm over practical ranges of correlation threshold specifications.",

author = "Zengyou He and Shengchun Deng and Xiaofei Xu",

year = "2005",

doi = "10.1007/11596448\_108",

language = "英语",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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He, Z, Deng, S & Xu, X 2005, An FP-tree based approach for mining all strongly correlated item pairs. in Computational Intelligence and Security - International Conference, CIS 2005, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3801 LNAI, pp. 735-740, International Conference on Computational Intelligence and Security, CIS 2005, Xi'an, China, 15/12/05. https://doi.org/10.1007/11596448_108

An FP-tree based approach for mining all strongly correlated item pairs. / He, Zengyou; Deng, Shengchun; Xu, Xiaofei.
Computational Intelligence and Security - International Conference, CIS 2005, Proceedings. 2005. p. 735-740 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3801 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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An FP-tree based approach for mining all strongly correlated item pairs

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