Incremental Closed Frequent Itemsets Mining-Based Approach Using Maximal Candidates

Incremental Closed Frequent Itemsets Mining-Based Approach Using Maximal Candidates

Incremental frequent itemset mining aims to efficiently update frequent itemsets without recalculating them from scratch, making it suitable for streaming data and real-time analytics. In the incremental frequent itemset mining approach, approximate methods are popular approaches that attempt to imp...

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Bibliographic Details
Main Authors: Mohammed A. Al-Zeiadi, Basheer M. Al-Maqaleh
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Incremental closed frequent itemsets
approximate approaches
maximal frequent itemsets
similarity measurements
maximal candidates itemsets
data-splitting methods
Online Access:https://ieeexplore.ieee.org/document/10892134/
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