Fast discovery of association rules
Advances in knowledge discovery and data mining
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Beyond Market Baskets: Generalizing Association Rules to Dependence Rules
Data Mining and Knowledge Discovery
The complexity of mining maximal frequent itemsets and maximal frequent patterns
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
TFP: An Efficient Algorithm for Mining Top-K Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
LCM ver.3: collaboration of array, bitmap and prefix tree for frequent itemset mining
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
An efficient rigorous approach for identifying statistically significant frequent itemsets
Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient incremental mining of top-K frequent closed itemsets
DS'07 Proceedings of the 10th international conference on Discovery science
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In this paper we introduce new algebraic forms, SOP+ and DSOP+, to represent functions f : {0,1}n → N, based on arithmetic sums of products. These expressions are a direct generalization of the classical SOP and DSOP forms. We propose optimal and heuristic algorithms for minimal SOP+ and DSOP+ synthesis. We then show how the DSOP+ form can be exploited for Data Mining applications. In particular we propose a new compact representation for the database of transactions to be used by the LCM algorithms for mining frequent closed itemsets.