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KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 4 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
CVPR
2011
IEEE
14 years 11 months ago
Mining Discriminative Co-occurrence Patterns for Visual Recognition
The co-occurrence pattern, a combination of binary or local features, is more discriminative than individual features and has shown its advantages in object, scene, and action rec...
Junsong Yuan, Ming Yang, Ying Wu
KDD
2009
ACM
188views Data Mining» more  KDD 2009»
16 years 4 months ago
Mining discrete patterns via binary matrix factorization
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Bao-Hong Shen, Shuiwang Ji, Jieping Ye
KDD
2001
ACM
1203views Data Mining» more  KDD 2001»
16 years 4 months ago
Application of Data Mining Techniques for Medical Image Classification
Breast cancer represents the second leading cause of cancer deaths in women today and it is the most common type of cancer in women. This paper presents some experiments for tumou...
Maria-Luiza Antonie, Osmar R. Zaïane, Alexand...
KDD
1999
ACM
147views Data Mining» more  KDD 1999»
15 years 8 months ago
Text Mining: Finding Nuggets in Mountains of Textual Data
Text mining appliesthe sameanalytical functions of datamining to the domainof textual information, relying on sophisticatedtext analysis techniques that distill information from f...
Jochen Dörre, Peter Gerstl, Roland Seiffert