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» Mining Frequent Itemsets from Uncertain Data
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FIMI
2003
88views Data Mining» more  FIMI 2003»
13 years 9 months ago
A fast APRIORI implementation
The efficiency of frequent itemset mining algorithms is determined mainly by three factors: the way candidates are generated, the data structure that is used and the implementati...
Ferenc Bodon
KDD
2008
ACM
246views Data Mining» more  KDD 2008»
14 years 8 months ago
Direct mining of discriminative and essential frequent patterns via model-based search tree
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
Wei Fan, Kun Zhang, Hong Cheng, Jing Gao, Xifeng Y...
AAAI
2006
13 years 9 months ago
Minimum Description Length Principle: Generators Are Preferable to Closed Patterns
The generators and the unique closed pattern of an equivalence class of itemsets share a common set of transactions. The generators are the minimal ones among the equivalent items...
Jinyan Li, Haiquan Li, Limsoon Wong, Jian Pei, Guo...
ICDE
2005
IEEE
118views Database» more  ICDE 2005»
14 years 9 months ago
Scrutinizing Frequent Pattern Discovery Performance
Benchmarking technical solutions is as important as the solutions themselves. Yet many fields still lack any type of rigorous evaluation. Performance benchmarking has always been ...
Mohammad El-Hajj, Osmar R. Zaïane, Stella Luk...
KDD
1999
ACM
217views Data Mining» more  KDD 1999»
13 years 12 months ago
An Efficient Algorithm to Update Large Itemsets with Early Pruning
We present an efficient algorithm (UWEP) for updating large itemsets when new transactions are added to the set of old transactions. UWEP employs a dynamic lookahead strategy in u...
Necip Fazil Ayan, Abdullah Uz Tansel, M. Erol Arku...