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KDD
2008
ACM
140views Data Mining» more  KDD 2008»
14 years 10 months ago
Semi-supervised approach to rapid and reliable labeling of large data sets
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
György J. Simon, Vipin Kumar, Zhi-Li Zhang
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
14 years 10 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
2006
ACM
155views Data Mining» more  KDD 2006»
14 years 10 months ago
Single-pass online learning: performance, voting schemes and online feature selection
To learn concepts over massive data streams, it is essential to design inference and learning methods that operate in real time with limited memory. Online learning methods such a...
Vitor R. Carvalho, William W. Cohen
KDD
2005
ACM
165views Data Mining» more  KDD 2005»
14 years 10 months ago
Co-clustering by block value decomposition
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
WWW
2010
ACM
14 years 5 months ago
Relational duality: unsupervised extraction of semantic relations between entities on the web
Extracting semantic relations among entities is an important first step in various tasks in Web mining and natural language processing such as information extraction, relation de...
Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuk...