An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets

Research article (Information Sciences, 2018) · cited 14× · AI/ML
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An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets

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An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-efficient-parallel-row-enumerated-algorithm-for-mining-frequent-colossal-closed-itemsets-from-high-dimensional-datase
MLA “An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-efficient-parallel-row-enumerated-algorithm-for-mining-frequent-colossal-closed-itemsets-from-high-dimensional-datase.
BibTeX @misc{4ortxyz_an-efficient-parallel-row-enumerated-algorithm-for-mining-frequent-colossal-closed-itemsets-from-high-dimensional-datase_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets}}, year = {2026}, url = {https://4ort.xyz/entity/an-efficient-parallel-row-enumerated-algorithm-for-mining-frequent-colossal-closed-itemsets-from-high-dimensional-datase}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An efficient parallel row enumerated algorithm for mining frequent colossal closed itemsets from high dimensional datasets — https://4ort.xyz/entity/an-efficient-parallel-row-enumerated-algorithm-for-mining-frequent-colossal-closed-itemsets-from-high-dimensional-datase (retrieved 2026-05-24)

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