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» Efficiently Mining Long Patterns from Databases
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ICDE
2001
IEEE
163views Database» more  ICDE 2001»
14 years 8 months ago
MAFIA: A Maximal Frequent Itemset Algorithm for Transactional Databases
We present a new algorithm for mining maximal frequent itemsets from a transactional database. Our algorithm is especially efficient when the itemsets in the database are very lon...
Douglas Burdick, Manuel Calimlim, Johannes Gehrke
BDA
2000
13 years 8 months ago
Incremental Mining of Sequential Patterns in Large Databases
In this paper we consider the problem of the incremental mining of sequential patterns when new transactions or new customers are added to an original database. We present a new a...
Florent Masseglia, Pascal Poncelet, Maguelonne Tei...
ICDE
2010
IEEE
750views Database» more  ICDE 2010»
13 years 11 months ago
Efficient and accurate discovery of patterns in sequence datasets
Existing sequence mining algorithms mostly focus on mining for subsequences. However, a large class of applications, such as biological DNA and protein motif mining, require effici...
Avrilia Floratou, Sandeep Tata, Jignesh M. Patel
EDBT
2002
ACM
157views Database» more  EDBT 2002»
14 years 7 months ago
Profit Mining: From Patterns to Actions
Abstract. A major obstacle in data mining applications is the gap between the statistic-based pattern extraction and the value-based decision making. We present a profit mining app...
Ke Wang, Senqiang Zhou, Jiawei Han
SDM
2004
SIAM
207views Data Mining» more  SDM 2004»
13 years 8 months ago
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint
Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation t...
Jianyong Wang, George Karypis