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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
150views Data Mining» more  KDD 2008»
15 years 10 months ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
KDD
2007
ACM
249views Data Mining» more  KDD 2007»
15 years 10 months ago
The minimum consistent subset cover problem and its applications in data mining
In this paper, we introduce and study the Minimum Consistent Subset Cover (MCSC) problem. Given a finite ground set X and a constraint t, find the minimum number of consistent sub...
Byron J. Gao, Martin Ester, Jin-yi Cai, Oliver Sch...
KDD
2006
ACM
139views Data Mining» more  KDD 2006»
15 years 10 months ago
Generating semantic annotations for frequent patterns with context analysis
As a fundamental data mining task, frequent pattern mining has widespread applications in many different domains. Research in frequent pattern mining has so far mostly focused on ...
Qiaozhu Mei, Dong Xin, Hong Cheng, Jiawei Han, Che...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
15 years 10 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
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