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PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 5 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
13 years 10 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...
ICDM
2007
IEEE
150views Data Mining» more  ICDM 2007»
13 years 11 months ago
Connections between Mining Frequent Itemsets and Learning Generative Models
Frequent itemsets mining is a popular framework for pattern discovery. In this framework, given a database of customer transactions, the task is to unearth all patterns in the for...
Srivatsan Laxman, Prasad Naldurg, Raja Sripada, Ra...
PKDD
2007
Springer
147views Data Mining» more  PKDD 2007»
13 years 11 months ago
MINI: Mining Informative Non-redundant Itemsets
Frequent itemset mining assists the data mining practitioner in searching for strongly associated items (and transactions) in large transaction databases. Since the number of frequ...
Arianna Gallo, Tijl De Bie, Nello Cristianini
SIGMOD
2000
ACM
129views Database» more  SIGMOD 2000»
13 years 9 months ago
Mining Frequent Patterns without Candidate Generation
Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous...
Jiawei Han, Jian Pei, Yiwen Yin