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KDD
2008
ACM
137views Data Mining» more  KDD 2008»
15 years 10 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
15 years 10 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...
KDD
2008
ACM
134views Data Mining» more  KDD 2008»
15 years 10 months ago
Privacy-preserving cox regression for survival analysis
Privacy-preserving data mining (PPDM) is an emergent research area that addresses the incorporation of privacy preserving concerns to data mining techniques. In this paper we prop...
Shipeng Yu, Glenn Fung, Rómer Rosales, Srir...
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
15 years 10 months ago
Detecting research topics via the correlation between graphs and texts
In this paper we address the problem of detecting topics in large-scale linked document collections. Recently, topic detection has become a very active area of research due to its...
Yookyung Jo, Carl Lagoze, C. Lee Giles
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
15 years 10 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...