Efficient Discovery of Association Rules in E-Commerce: Comparing Candidate Generation and Pattern Growth Techniques

Efficient Discovery of Association Rules in E-Commerce: Comparing Candidate Generation and Pattern Growth Techniques

Association rule mining plays a critical role in uncovering item correlations and hidden patterns within transactional data, particularly in e-commerce environments. Despite the widespread use of Apriori and FP-Growth algorithms, few studies offer a statistically rigorous, tool-based comparison of t...

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Bibliographic Details
Main Authors: Ioan Daniel Hunyadi, Nicolae Constantinescu, Oana-Adriana Țicleanu
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
Subjects:
association rule mining
Apriori algorithm
FP-Growth algorithm
e-commerce data mining
frequent itemsets
comparative analysis
Online Access:https://www.mdpi.com/2076-3417/15/10/5498
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