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AUSAI
2008
Springer
13 years 10 months ago
Learning to Find Relevant Biological Articles without Negative Training Examples
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
Keith Noto, Milton H. Saier Jr., Charles Elkan
JMLR
2010
172views more  JMLR 2010»
13 years 3 months ago
Modeling annotator expertise: Learning when everybody knows a bit of something
Supervised learning from multiple labeling sources is an increasingly important problem in machine learning and data mining. This paper develops a probabilistic approach to this p...
Yan Yan, Rómer Rosales, Glenn Fung, Mark W....
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
14 years 2 months ago
Hierarchy-Regularized Latent Semantic Indexing
Organizing textual documents into a hierarchical taxonomy is a common practice in knowledge management. Beside textual features, the hierarchical structure of directories reflect...
Yi Huang, Kai Yu, Matthias Schubert, Shipeng Yu, V...
ECML
2007
Springer
14 years 13 days ago
Finding Composite Episodes
Mining frequent patterns is a major topic in data mining research, resulting in many seminal papers and algorithms on item set and episode discovery. The combination of these, call...
Ronnie Bathoorn, Arno Siebes
KDD
2008
ACM
128views Data Mining» more  KDD 2008»
14 years 9 months ago
Scaling up text classification for large file systems
: We combine the speed and scalability of information retrieval with the generally superior classification accuracy offered by machine learning, yielding a two-phase text classifie...
George Forman, Shyamsundar Rajaram