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KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 7 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
KDD
2003
ACM
99views Data Mining» more  KDD 2003»
16 years 7 months ago
Fragments of order
High-dimensional collections of 0-1 data occur in many applications. The attributes in such data sets are typically considered to be unordered. However, in many cases there is a n...
Aristides Gionis, Teija Kujala, Heikki Mannila
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 7 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
KDD
2009
ACM
172views Data Mining» more  KDD 2009»
16 years 7 months ago
Towards combining web classification and web information extraction: a case study
: ? Towards Combining Web Classification and Web Information Extraction: a Case Study Ping Luo, Fen Lin, Yuhong Xiong, Yong Zhao, Zhongzhi Shi HP Laboratories HPL-2009-86 Classific...
Ping Luo, Fen Lin, Yuhong Xiong, Yong Zhao, Zhongz...
KDD
2009
ACM
158views Data Mining» more  KDD 2009»
16 years 7 months ago
Feature shaping for linear SVM classifiers
: ? Feature Shaping for Linear SVM Classifiers George Forman, Martin Scholz, Shyamsundar Rajaram HP Laboratories HPL-2009-31R1 text classification machine learning, feature weighti...
George Forman, Martin Scholz, Shyamsundar Rajaram