Inverted Index Automata Frequent Itemset Mining for Large Dataset Frequent Itemset Mining

Inverted Index Automata Frequent Itemset Mining for Large Dataset Frequent Itemset Mining

Frequent itemset mining (FIM) faces significant challenges with the expansion of large-scale datasets. Traditional algorithms such as Apriori, FP-Growth, and Eclat suffer from poor scalability and low efficiency when applied to modern datasets characterized by high dimensionality and high-density fe...

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Bibliographic Details
Main Authors: Xin Dai, Haza Nuzly Abdull Hamed, Qichen Su, Xue Hao
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Frequent itemset mining
inverted index
finite automata
depth-first search
large-scale data analysis
Online Access:https://ieeexplore.ieee.org/document/10811914/
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https://ieeexplore.ieee.org/document/10811914/

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