PKDD
2004
Springer
14 years 6 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
14 years 6 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
14 years 7 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
14 years 7 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
14 years 7 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
14 years 8 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...