research-article

Exploring Decomposition for Solving Pattern Mining Problems

Authors:

Youcef Djenouri,

Jerry Chun-Wei Lin,

Kjetil Nørvåg,

Heri Ramampiaro,

Philip S. YuAuthors Info & Claims

ACM Transactions on Management Information Systems (TMIS), Volume 12, Issue 2

Article No.: 15, Pages 1 - 36

https://doi.org/10.1145/3439771

Published: 11 February 2021 Publication History

Abstract

This article introduces a highly efficient pattern mining technique called Clustering-based Pattern Mining (CBPM). This technique discovers relevant patterns by studying the correlation between transactions in the transaction database based on clustering techniques. The set of transactions is first clustered, such that highly correlated transactions are grouped together. Next, we derive the relevant patterns by applying a pattern mining algorithm to each cluster. We present two different pattern mining algorithms, one applying an approximation-based strategy and another based on an exact strategy. The approximation-based strategy takes into account only the clusters, whereas the exact strategy takes into account both clusters and shared items between clusters. To boost the performance of the CBPM, a GPU-based implementation is investigated. To evaluate the CBPM framework, we perform extensive experiments on several pattern mining problems. The results from the experimental evaluation show that the CBPM provides a reduction in both the runtime and memory usage. Also, CBPM based on the approximate strategy provides good accuracy, demonstrating its effectiveness and feasibility. Our GPU implementation achieves significant speedup of up to 552× on a single GPU using big transaction databases.

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Cited By

Bobed Lisbona CBernad JMaillot P(2024)Language-Model Based Informed Partition of Databases to Speed Up Pattern MiningProceedings of the ACM on Management of Data10.1145/36549872:3(1-27)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654987
Belhadi AZhang MArcuri A(2024)Random Testing and Evolutionary Testing for Fuzzing GraphQL APIsACM Transactions on the Web10.1145/360942718:1(1-41)Online publication date: 5-Jan-2024
https://dl.acm.org/doi/10.1145/3609427
Brathovde KDjenouri YYazidi ASrivastava G(2024)Intelligent Customer Behaviour Analysis in the Norwegian Market2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW61823.2024.00014(71-77)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDEW61823.2024.00014
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Index Terms

Exploring Decomposition for Solving Pattern Mining Problems
1. Computing methodologies
  1. Artificial intelligence
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Transactions on Management Information Systems

ACM Transactions on Management Information Systems Volume 12, Issue 2

June 2021

227 pages

ISSN:2158-656X

EISSN:2158-6578

DOI:10.1145/3446838

Editor:
Daniel Zeng
Chinese Academy of Sciences, China

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Publication History

Published: 11 February 2021

Accepted: 01 November 2020

Revised: 01 October 2020

Received: 01 April 2020

Published in TMIS Volume 12, Issue 2

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https://dl.acm.org/doi/10.1145/3654987
Belhadi AZhang MArcuri A(2024)Random Testing and Evolutionary Testing for Fuzzing GraphQL APIsACM Transactions on the Web10.1145/360942718:1(1-41)Online publication date: 5-Jan-2024
https://dl.acm.org/doi/10.1145/3609427
Brathovde KDjenouri YYazidi ASrivastava G(2024)Intelligent Customer Behaviour Analysis in the Norwegian Market2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW)10.1109/ICDEW61823.2024.00014(71-77)Online publication date: 13-May-2024
https://doi.org/10.1109/ICDEW61823.2024.00014
Zhao XZhong XHan B(2024)Frequent Closed High-Utility Itemset Mining Algorithm Based on Leiden Community Detection and Compact Genetic AlgorithmIEEE Access10.1109/ACCESS.2024.341396612(84763-84773)Online publication date: 2024
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Djenouri YBelhadi ASrivastava GLin J(2023)Advanced Pattern-Mining System for Fake News AnalysisIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.323340810:6(2949-2958)Online publication date: Dec-2023
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Liu XZheng LZhang WZhou JCao SYu S(2022)An Evolutive Frequent Pattern Tree-based Incremental Knowledge Discovery AlgorithmACM Transactions on Management Information Systems10.1145/349521313:3(1-20)Online publication date: 4-Feb-2022
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Fouad MHussein WRady SYu PGharib T(2022)An Efficient Approach for Mining Reliable High Utility PatternsIEEE Access10.1109/ACCESS.2021.313902810(1419-1431)Online publication date: 2022
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