Graph-Based Algorithms for Boolean Function Manipulation
IEEE Transactions on Computers
Shared binary decision diagram with attributed edges for efficient Boolean function manipulation
DAC '90 Proceedings of the 27th ACM/IEEE Design Automation Conference
Binary decision diagrams and applications for VLSI CAD
Binary decision diagrams and applications for VLSI CAD
Algebraic decision diagrams and their applications
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Efficiently mining long patterns from databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Turbo-charging vertical mining of large databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
Efficiently Mining Maximal Frequent Itemsets
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
The Complexity of the Optimal Variable Ordering Problems of Shared Binary Decision Diagrams
ISAAC '93 Proceedings of the 4th International Symposium on Algorithms and Computation
Fast vertical mining using diffsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
GenMax: An Efficient Algorithm for Mining Maximal Frequent Itemsets
Data Mining and Knowledge Discovery
IEEE Transactions on Computers
Estimation of the density of datasets with decision diagrams
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
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In this paper, we mainly address the problem of loading transaction datasets into main memory and estimating the density of such datasets. We propose BOOLLOADER, an algorithm dedicated to these tasks; it relies on a compressed representation of all the transactions of the dataset. For sake of efficiency, we have chosen Decision Diagrams as the main data structure to the representation of datasets into memory. We give an experimental evaluation of our algorithm on both dense and sparse datasets. Experiments have shown that BOOLLOADER is efficient for loading some dense datasets and gives a partial answer about the nature of the dataset before time-consuming pattern extraction tasks. We further investigate the use of Algebraic Decision Diagrams by studying the feasibility of current Data Mining operations, as for instance computing the support of an itemset and even mining frequent itemsets.