Sciweavers

704 search results - page 3 / 141
» Discovering Itemset Interactions
Sort
View
AI
2001
Springer
13 years 10 months ago
A Low-Scan Incremental Association Rule Maintenance Method Based on the Apriori Property
As new transactions update data sources and subsequently the data warehouse, the previously discovered association rules in the old database may no longer be interesting rules in ...
Zequn Zhou, C. I. Ezeife
ICSM
2007
IEEE
14 years 17 days ago
Discovering Dynamic Developer Relationships from Software Version Histories by Time Series Segmentation
Time series analysis is a promising approach to discover temporal patterns from time stamped, numeric data. A novel approach to apply time series analysis to discern temporal info...
Harvey P. Siy, Parvathi Chundi, Daniel J. Rosenkra...
RCIS
2010
13 years 4 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—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,...
Jia-Ling Koh, Yi-Lang Tu
CIDM
2007
IEEE
14 years 19 days ago
Measuring the Validity of Document Relations Discovered from Frequent Itemset Mining
— The extension approach of frequent itemset mining can be applied to discover the relations among documents. Several schemes, i.e., n-gram, stemming, stopword removal and term w...
Kritsada Sriphaew, Thanaruk Theeramunkong
KES
2004
Springer
13 years 11 months ago
FIT: A Fast Algorithm for Discovering Frequent Itemsets in Large Databases
Association rule mining is an important data mining problem that has been studied extensively. In this paper, a simple but Fast algorithm for Intersecting attribute lists using a ...
Jun Luo, Sanguthevar Rajasekaran