Optimization of frequent item set mining parallelization algorithm based on spark platform

In this paper, we propose a new method that combines the parallelism of the Spark-based platform with fast frequent mining, called STB_Apriori. Previous research has shown that traditional frequent itemset mining algorithms have high overhead when faced with large datasets and high-dimensional data...

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Bibliographic Details

Published in:	Information retrieval (Boston) Vol. 27; no. 1; p. 38
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Nature B.V 02.11.2024
Subjects:	Algorithms Boolean Clustering Data compression Data mining Datasets Distributed processing Efficiency Parallel processing Python Social networks User requirements
ISSN:	1386-4564, 1573-7659
Online Access:	Get full text
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