New algorithms for efficient mining of association rules

Li Shen, Hong Shen, Ling Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Discovery of association rules is an important data mining task. Several algorithms have been proposed to solve this problem. Most of them require repeated passes over the database, which incurs huge I/O overhead and high synchronization expense in parallel cases. There are a few algorithms trying to reduce these costs. But they contains weaknesses such as often requiring high pre-processing cost to get a vertical database layout, containing much redundant computation in parallel cases, and so on. We propose new association mining algorithms to overcome the above drawbacks: through minimizing the I/O cost and effectively controlling the computation cost. Experiments on well-known synthetic data show that our algorithms consistently outperform a priori, one of the best algorithms for association mining, by factors ranging from 2 to 4 in most cases. Also, our algorithms are very easy to be parallelized, and we present a parallelization for them based on a shared-nothing architecture. We observe that the parallelism in our parallel approach is developed more sufficiently than in two of the best existing parallel algorithms.

Original languageEnglish (US)
Title of host publicationProceedings - Frontiers 1999, 7th Symposium on the Frontiers of Massively Parallel Computation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages234-241
Number of pages8
ISBN (Electronic)0769500870, 9780769500874
DOIs
StatePublished - Jan 1 1999
Externally publishedYes
Event7th Symposium on the Frontiers of Massively Parallel Computation, Frontiers 1999 - Annapolis, United States
Duration: Feb 21 1999Feb 25 1999

Other

Other7th Symposium on the Frontiers of Massively Parallel Computation, Frontiers 1999
CountryUnited States
CityAnnapolis
Period2/21/992/25/99

Fingerprint

Association rules
Association Rules
Mining
Costs
Synthetic Data
Parallel algorithms
Parallelization
Parallel Algorithms
Parallelism
Data mining
Preprocessing
Layout
Data Mining
Synchronization
Vertical
Processing
Experiment
Experiments

Keywords

  • association rule
  • data mining
  • frequent itemset
  • parallel processing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Modeling and Simulation

Cite this

Shen, L., Shen, H., & Cheng, L. (1999). New algorithms for efficient mining of association rules. In Proceedings - Frontiers 1999, 7th Symposium on the Frontiers of Massively Parallel Computation (pp. 234-241). [750605] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FMPC.1999.750605

New algorithms for efficient mining of association rules. / Shen, Li; Shen, Hong; Cheng, Ling.

Proceedings - Frontiers 1999, 7th Symposium on the Frontiers of Massively Parallel Computation. Institute of Electrical and Electronics Engineers Inc., 1999. p. 234-241 750605.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shen, L, Shen, H & Cheng, L 1999, New algorithms for efficient mining of association rules. in Proceedings - Frontiers 1999, 7th Symposium on the Frontiers of Massively Parallel Computation., 750605, Institute of Electrical and Electronics Engineers Inc., pp. 234-241, 7th Symposium on the Frontiers of Massively Parallel Computation, Frontiers 1999, Annapolis, United States, 2/21/99. https://doi.org/10.1109/FMPC.1999.750605
Shen L, Shen H, Cheng L. New algorithms for efficient mining of association rules. In Proceedings - Frontiers 1999, 7th Symposium on the Frontiers of Massively Parallel Computation. Institute of Electrical and Electronics Engineers Inc. 1999. p. 234-241. 750605 https://doi.org/10.1109/FMPC.1999.750605
Shen, Li ; Shen, Hong ; Cheng, Ling. / New algorithms for efficient mining of association rules. Proceedings - Frontiers 1999, 7th Symposium on the Frontiers of Massively Parallel Computation. Institute of Electrical and Electronics Engineers Inc., 1999. pp. 234-241
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