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KDD
2008
ACM
181views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
KDD
2008
ACM
135views Data Mining» more  KDD 2008»
16 years 7 months ago
DiMaC: a disguised missing data cleaning tool
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially va...
Ming Hua, Jian Pei
187
Voted
KDD
2008
ACM
199views Data Mining» more  KDD 2008»
16 years 7 months ago
Efficient computation of personal aggregate queries on blogs
There is an exploding amount of user-generated content on the Web due to the emergence of "Web 2.0" services, such as Blogger, MySpace, Flickr, and del.icio.us. The part...
Ka Cheung Sia, Junghoo Cho, Yun Chi, Belle L. Tsen...
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
16 years 7 months ago
Learning from multi-topic web documents for contextual advertisement
Contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. Often advertisers wish to either target (or avoid) ...
Yi Zhang, Arun C. Surendran, John C. Platt, Mukund...
219
Voted
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 7 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