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KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 7 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
KDD
2006
ACM
118views Data Mining» more  KDD 2006»
16 years 7 months ago
Reducing the human overhead in text categorization
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
Arnd Christian König, Eric Brill
KDD
2006
ACM
141views Data Mining» more  KDD 2006»
16 years 7 months ago
Statistical entity-topic models
The primary purpose of news articles is to convey information about who, what, when and where. But learning and summarizing these relationships for collections of thousands to mil...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...
KDD
2006
ACM
183views Data Mining» more  KDD 2006»
16 years 7 months ago
Discovering interesting patterns through user's interactive feedback
In this paper, we study the problem of discovering interesting patterns through user's interactive feedback. We assume a set of candidate patterns (i.e., frequent patterns) h...
Dong Xin, Xuehua Shen, Qiaozhu Mei, Jiawei Han
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
16 years 7 months ago
Formulating distance functions via the kernel trick
Tasks of data mining and information retrieval depend on a good distance function for measuring similarity between data instances. The most effective distance function must be for...
Gang Wu, Edward Y. Chang, Navneet Panda