ICDM
2005
IEEE
14 years 6 months ago
2005
IEEE
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to...
ADC
2006
Springer
14 years 6 months ago
2006
Springer
Frequent itemsets mining is well explored for various data types, and its computational complexity is well understood. Based on our previous work by Nguyen and Orlowska (2005), th...
PKDD
2007
Springer
14 years 6 months ago
2007
Springer
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...
AUSDM
2007
Springer
14 years 6 months ago
2007
Springer
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
ICDM
2007
IEEE
14 years 6 months ago
2007
IEEE
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...
ICDM
2007
IEEE
14 years 6 months ago
2007
IEEE
We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency ove...
IEAAIE
2009
Springer
14 years 7 months ago
2009
Springer
Data mining refers to the process of revealing unknown and potentially useful information from a large database. Frequent itemsets mining is one of the foundational problems in dat...
KDD
2009
ACM
14 years 7 months ago
2009
ACM
In this paper, we consider a novel scheme referred to as Cartesian contour to concisely represent the collection of frequent itemsets. Different from the existing works, this sche...
PODS
2003
ACM
15 years 17 days ago
2003
ACM
Computing frequent itemsets and maximally frequent itemsets in a database are classic problems in data mining. The resource requirements of all extant algorithms for both problems...
KDD
2004
ACM
15 years 26 days ago
2004
ACM
The paper presents a method for pruning frequent itemsets based on background knowledge represented by a Bayesian network. The interestingness of an itemset is defined as the abso...