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» Mining negative association rules
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SEMCO
2008
IEEE
15 years 6 months ago
Text Categorization Based on Boosting Association Rules
Associative classification is a novel and powerful method originating from association rule mining. In the previous studies, a relatively small number of high-quality association...
Yongwook Yoon, Gary Geunbae Lee
ISBRA
2009
Springer
15 years 6 months ago
Mining of cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing
KIM, JIHYE. Mining of Cis-Regulatory Motifs Associated with Tissue-Specific Alternative Splicing. (Under the direction of Steffen Heber). Alternative splicing (AS) is an important...
Jihye Kim, Sihui Zhao, Brian E. Howard, Steffen He...
AUSAI
2006
Springer
15 years 3 months ago
Incorporating Pageview Weight into an Association-Rule-Based Web Recommendation System
Web recommendation systems based on web usage mining try to mine users' behavior patterns from web access logs, and recommend pages to the online user by matching the user...
Liang Yan, Chunping Li
FLAIRS
2008
15 years 2 months ago
Semantic Analysis of Association Rules
When applying association mining to real datasets, a major obstacle is that often a huge number of rules are generated even with very reasonable support and confidence. Among thes...
Ping Chen, Rakesh M. Verma, Janet C. Meininger, We...
PAKDD
2005
ACM
94views Data Mining» more  PAKDD 2005»
15 years 5 months ago
Progressive Sampling for Association Rules Based on Sampling Error Estimation
We explore in this paper a progressive sampling algorithm, called Sampling Error Estimation (SEE), which aims to identify an appropriate sample size for mining association rules. S...
Kun-Ta Chuang, Ming-Syan Chen, Wen-Chieh Yang