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» Learning Classifiers from Semantically Heterogeneous Data
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EXPERT
2008
134views more  EXPERT 2008»
13 years 7 months ago
Learning to Tag and Tagging to Learn: A Case Study on Wikipedia
Natural language technologies have been long envisioned to play a crucial role in transitioning from the current Web to a more "semantic" Web. If anything, the significa...
Peter Mika, Massimiliano Ciaramita, Hugo Zaragoza,...
MICAI
2010
Springer
13 years 6 months ago
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
Mahdi Tabassian, Reza Ghaderi, Reza Ebrahimpour
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
14 years 8 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
NAACL
2007
13 years 9 months ago
Extracting Semantic Orientations of Phrases from Dictionary
We propose a method for extracting semantic orientations of phrases (pairs of an adjective and a noun): positive, negative, or neutral. Given an adjective, the semantic orientatio...
Hiroya Takamura, Takashi Inui, Manabu Okumura
CVPR
2004
IEEE
14 years 9 months ago
Feature Selection for Classifying High-Dimensional Numerical Data
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...
Yimin Wu, Aidong Zhang