A critical review of deep learning algorithm in association rule mining | [Journal of Theoretical and Applied Information Technology • 2022]

Author(s):

1. WAN AEZWANI WAN ABU BAKAR: Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, 22200, Besut, Terengganu, Malaysia

2. MUHAMAD AMIERUSYAHMI ZUHAIRI: Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, 22200, Besut, Terengganu, Malaysia

3. MUSTAFA MAN: Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia

4. JULAILY AIDA JUSOH: Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut Campus, 22200, Besut, Terengganu, Malaysia

5. YAYA SUDARYA TRIANA: Faculty of Computer Science, Universitas Mercu Buana, Jakarta, Indonesia

Abstract:

Data mining, an urging requirement within the current era and whose scope of research is predicted to be for upcoming decades. Among the competent techniques of data mining association rule mining plays an amazing role. This technique indicates on curious association, correlations and frequent patterns from the given data sources to be mined. The primary goal of association mining is to find common patterns and investigate association rules. There are a variety of association rule mining algorithms available, each with its own set of performance factors. Advanced of the association rules data structure format based on horizontal or vertical. Both structure formats are extensively applied in several association rule algorithm to attain the least execution time and minimum memory consumption. One of the established algorithms for association is Equivalence Class Transformation (Eclat). Deep learning (DL) has exploded as the current technology for mining of large amount of data from sources such as social media, internet, e-commerce, and online movie theatres. This massive volume of information is easily accessible and can share via cloud computing. In response to big data mining issues, the DL algorithm is recognized to be the most potential techniques when it reaches to association rule pattern generation. In this paper, we reviewed and analyzed the fundamental Eclat algorithm in DL. These reviews would determine some alternative approaches of deep learning techniques may be adopted in Eclat to boost the least execution time and reduce memory.

Page(s): 1487-1494

DOI: DOI not available

Published: Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 5, Year: 2022

Keywords:

Deep Learning DL , Association Rule Mining , Frequent itemset , Eclat algorithm

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