148 search results - page 7 / 30 » Mining top-K frequent itemsets from data streams |
KDD
2004
ACM
14 years 9 months 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...
ICDM
2002
IEEE
14 years 1 months ago
2002
IEEE
Mining of frequent itemsets is a fundamental data mining task. Past research has proposed many efficient algorithms for the purpose. Recent work also highlighted the importance of...
RCIS
2010
13 years 7 months ago
2010
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
AUSDM
2007
Springer
14 years 2 months ago
2007
Springer
Mining High Utility Itemsets from a transaction database is to find itemsests that have utility above a user-specified threshold. This problem is an extension of Frequent Itemset ...
KDD
2007
ACM
14 years 9 months ago
2007
ACM
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....