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KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 7 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
144
Voted
KDD
2004
ACM
112views Data Mining» more  KDD 2004»
16 years 7 months ago
A rank sum test method for informative gene discovery
Finding informative genes from microarray data is an important research problem in bioinformatics research and applications. Most of the existing methods rank features according t...
Lin Deng, Jian Pei, Jinwen Ma, Dik Lun Lee
KDD
2004
ACM
154views Data Mining» more  KDD 2004»
16 years 7 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 7 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
KDD
2004
ACM
209views Data Mining» more  KDD 2004»
16 years 7 months ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi