Multilevel rules mining association for processing big data using genetic algorithm

Gebeyehu Belay  Gebremeskel; Teshale Wubie  Yilma

doi:10.59400/cai1819

Multilevel rules mining association for processing big data using genetic algorithm

Gebeyehu Belay Gebremeskel Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar PO BOX 26, Ethiopia
Teshale Wubie Yilma Department of Computer Science, Informatics College, Debre Tabor University, Debra Tabor PO BOX 272, Ethiopia

Article ID: 1819

DOI: https://doi.org/10.59400/cai1819

Keywords: data mining; market basket data; genetic algorithm; association rules; apriori algorithm; optimization

Abstract

Data mining is a machine learning method and a subset of artificial intelligence that focuses on developing algorithms to enable a computer to learn from data and past experiences within its context. Multilevel association rules mining is a crucial area for discovering interesting relationships between data elements at various levels of abstraction. Many existing algorithms addressing this issue rely on exhaustive search methods such as Apriori and FP-growth. However, these methods incur significant computational costs when applied to big data applications searching for association rules. Therefore, we propose a novel genetic-based method with three key innovations to speed up the search for multilevel association rules and reduce excessive computation. Firstly, we utilize the category tree to describe multilevel application data sets as domain knowledge. Next, we introduce a unique tree-encoding schema based on the category tree to develop the heuristic multilevel association-mining algorithm. Lastly, we present a genetic algorithm based on the tree-encoding schema that greatly decreases the association rule search space. This method is valuable for mining multilevel association rules in big data applications.

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Published

2025-02-25

How to Cite

Gebremeskel, G. B., & Yilma, T. W. (2025). Multilevel rules mining association for processing big data using genetic algorithm. Computing and Artificial Intelligence, 3(1), 1819. https://doi.org/10.59400/cai1819

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