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» Parallel Mining of Maximal Frequent Itemsets from Databases
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ICTAI
2003
IEEE
13 years 9 months ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo
FIMI
2004
239views Data Mining» more  FIMI 2004»
13 years 6 months ago
LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets
: For a transaction database, a frequent itemset is an itemset included in at least a specified number of transactions. A frequent itemset P is maximal if P is included in no other...
Takeaki Uno, Masashi Kiyomi, Hiroki Arimura
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
13 years 9 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
ICDE
2001
IEEE
163views Database» more  ICDE 2001»
14 years 5 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