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» Feature Extraction for Massive Data Mining
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BMCBI
2010
154views more  BMCBI 2010»
14 years 9 months ago
EnvMine: A text-mining system for the automatic extraction of contextual information
Background: For ecological studies, it is crucial to count on adequate descriptions of the environments and samples being studied. Such a description must be done in terms of thei...
Javier Tamames, Victor de Lorenzo
KDD
2005
ACM
218views Data Mining» more  KDD 2005»
15 years 10 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
15 years 3 months ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti
KDD
2004
ACM
160views Data Mining» more  KDD 2004»
15 years 10 months ago
Boosting for Text Classification with Semantic Features
Abstract. Current text classification systems typically use term stems for representing document content. Semantic Web technologies allow the usage of features on a higher semantic...
Stephan Bloehdorn, Andreas Hotho
82
Voted
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
15 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