Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
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
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
Proceedings of the 17th International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Towards Efficient Re-mining of Frequent Patterns upon Threshold Changes
WAIM '02 Proceedings of the Third International Conference on Advances in Web-Age Information Management
Towards Efficient Data Re-mining (DRM)
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Data Organization and Access for Efficient Data Mining
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
CLOSET+: searching for the best strategies for mining frequent closed itemsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast vertical mining using diffsets
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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There have been many studies on efficient discovery of frequent itemsets in large databases. However, it is nontrivial to mine frequent itemsets under interactive circumstances where users often change minimum support threshold (minsup) because the change of minsup may invalidate existing frequent itemsets or introduce new frequent itemsets. In this paper, we propose an efficient interactive mining technique based on a novel vertical itemset tree (VI-tree) structure. An important feature of our algorithm is that it does not have to re-examine the existing frequent itemsets when minsup becomes small. Such feature makes it very efficient for interactive mining. The algorithm we proposed has been implemented and its performance is compared with re-running Eclat, a vertical mining algorithm, under different minsup. Experimental results show that our algorithm is over two orders of magnitude faster than the latter in average.