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RCIS
2010
15 years 5 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
KDD
2003
ACM
144views Data Mining» more  KDD 2003»
16 years 7 months ago
Clinical and financial outcomes analysis with existing hospital patient records
Existing patient records are a valuable resource for automated outcomes analysis and knowledge discovery. However, key clinical data in these records is typically recorded in unst...
R. Bharat Rao, Sathyakama Sandilya, Radu Stefan Ni...
CVPR
2008
IEEE
16 years 9 months ago
Mining compositional features for boosting
The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the t...
Junsong Yuan, Jiebo Luo, Ying Wu
WWW
2006
ACM
16 years 8 months ago
Mining search engine query logs for query recommendation
This paper presents a simple and intuitive method for mining search engine query logs to get fast query recommendations on a large scale industrial-strength search engine. In orde...
Zhiyong Zhang, Olfa Nasraoui
ADC
2003
Springer
182views Database» more  ADC 2003»
16 years 14 days ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan