PKDD
2004
Springer
13 years 9 months ago
2004
Springer
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
CINQ
2004
Springer
13 years 9 months ago
2004
Springer
Algorithms for finding frequent itemsets fall into two broad classes: (1) algorithms that are based on non-trivial SQL statements to query and update a database, and (2) algorithms...
ICDM
2005
IEEE
13 years 10 months ago
2005
IEEE
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
SAC
2006
ACM
13 years 10 months ago
2006
ACM
We propose a method for induction of compact optimal recommendation policies based on discovery of frequent itemsets in a purchase database, followed by the application of standar...
ICTAI
2007
IEEE
13 years 10 months ago
2007
IEEE
We describe here a general approach for rare itemset mining. While mining literature has been almost exclusively focused on frequent itemsets, in many practical situations rare on...
CIKM
2009
Springer
13 years 11 months ago
2009
Springer
Mining frequent itemsets in data streams is beneficial to many real-world applications but is also a challenging task since data streams are unbounded and have high arrival rates...