The paper restates the standard Boolean matrix (vertical bit-vector) approach to frequent itemset mining and reports self-measured runtime and memory on the Groceries dataset without any baseline comparison.
Probabilistic Support Prediction: Fast frequent itemset mining in dense data,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.DB 1years
2024 1verdicts
REJECT 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets
The paper restates the standard Boolean matrix (vertical bit-vector) approach to frequent itemset mining and reports self-measured runtime and memory on the Groceries dataset without any baseline comparison.