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NIPS
2008
13 years 6 months ago
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
Yi Zhang 0010, Jeff Schneider, Artur Dubrawski
ACL
2009
13 years 3 months ago
Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm
Most of previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with the prosodic lab...
Je Hun Jeon, Yang Liu
ICPR
2010
IEEE
13 years 3 months ago
Enhancing Web Page Classification via Local Co-training
Abstract--In this paper we propose a new multi-view semisupervised learning algorithm called Local Co-Training (LCT). The proposed algorithm employs a set of local models with vect...
Youtian Du, Xiaohong Guan, Zhongmin Cai
ECML
2001
Springer
13 years 9 months ago
Classification on Data with Biased Class Distribution
Labeled data for classification could often be obtained by sampling that restricts or favors choice of certain classes. A classifier trained using such data will be biased, resulti...
Slobodan Vucetic, Zoran Obradovic
DASFAA
2004
IEEE
135views Database» more  DASFAA 2004»
13 years 9 months ago
Semi-supervised Text Classification Using Partitioned EM
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...
Gao Cong, Wee Sun Lee, Haoran Wu, Bing Liu