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Data Association Rules Mining Method Based on Improved Apriori Algorithm

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Haotong WuAuthors Info & Claims

ICBDR '20: Proceedings of the 4th International Conference on Big Data Research

Pages 12 - 17

https://doi.org/10.1145/3445945.3445948

Published: 01 March 2021 Publication History

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Abstract

In the existing data mining technology, there are some shortcomings in association rule mining methods. In this paper, aiming at the problem that the mining efficiency of Apriori algorithm is not high when dealing with large database, the genetic algorithm is introduced to improve the Apriori algorithm. This paper first introduces the basic concept and principle of association rules, describes the basic idea of Apriori algorithm in detail, and an improved algorithm based on Partition algorithm is proposed for its shortcomings. Then introducing the principle and operation flow of genetic algorithm in detail, and puts forward the corresponding improvement solutions for the coding scheme and fitness function. Finally, the association rule mining is established by combining genetic algorithm with Apriori algorithm. Compared with other methods, the experimental results show that the proposed method has better performance, higher mining efficiency and better data mining.

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Cited By

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Aljehani SAlotaibi Y(2024)Preserving Privacy in Association Rule Mining Using Metaheuristic-Based Algorithms: A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2024.336290712(21217-21236)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3362907
Sundarakumar MSharma RFathima SGokul Rajan VDhayanithi JMarimuthu MMohanraj GSharma AJohny Renoald A(2023)Improving Data Processing Speed on Large Datasets in a Hadoop Multi-node Cluster using Enhanced Apriori AlgorithmJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23204845:4(6161-6177)Online publication date: 4-Oct-2023
https://doi.org/10.3233/JIFS-232048
Tran DHuh J(2023)Forecast of seasonal consumption behavior of consumers and privacy-preserving data mining with new S-Apriori algorithmThe Journal of Supercomputing10.1007/s11227-023-05105-679:11(12691-12736)Online publication date: 18-Mar-2023
https://doi.org/10.1007/s11227-023-05105-6
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ICBDR '20: Proceedings of the 4th International Conference on Big Data Research

November 2020

110 pages

ISBN:9781450387750

DOI:10.1145/3445945

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 March 2021

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ICBDR 2020: 2020 the 4th International Conference on Big Data Research

November 27 - 29, 2020

Tokyo, Japan

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Aljehani SAlotaibi Y(2024)Preserving Privacy in Association Rule Mining Using Metaheuristic-Based Algorithms: A Systematic Literature ReviewIEEE Access10.1109/ACCESS.2024.336290712(21217-21236)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3362907
Sundarakumar MSharma RFathima SGokul Rajan VDhayanithi JMarimuthu MMohanraj GSharma AJohny Renoald A(2023)Improving Data Processing Speed on Large Datasets in a Hadoop Multi-node Cluster using Enhanced Apriori AlgorithmJournal of Intelligent & Fuzzy Systems10.3233/JIFS-23204845:4(6161-6177)Online publication date: 4-Oct-2023
https://doi.org/10.3233/JIFS-232048
Tran DHuh J(2023)Forecast of seasonal consumption behavior of consumers and privacy-preserving data mining with new S-Apriori algorithmThe Journal of Supercomputing10.1007/s11227-023-05105-679:11(12691-12736)Online publication date: 18-Mar-2023
https://doi.org/10.1007/s11227-023-05105-6
Kannout ENguyen HGrzegorowski M(2022)Speeding Up Recommender Systems Using Association RulesIntelligent Information and Database Systems10.1007/978-3-031-21967-2_14(167-179)Online publication date: 28-Nov-2022
https://dl.acm.org/doi/10.1007/978-3-031-21967-2_14

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Mining Association Rules Based on Apriori Algorithm and Application

Efficient algorithm for the extraction of association rules in data mining

An Improved Apriori-based Algorithm for Association Rules Mining

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