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COLING
2010
14 years 10 months ago
Improving Name Origin Recognition with Context Features and Unlabelled Data
We demonstrate the use of context features, namely, names of places, and unlabelled data for the detection of personal name language of origin. While some early work used either r...
Vladimir Pervouchine, Min Zhang, Ming Liu, Haizhou...
174
Voted
ICDM
2009
IEEE
184views Data Mining» more  ICDM 2009»
15 years 1 months ago
Improved Multi Label Classification in Hierarchical Taxonomies
Hierarchical taxonomies are used to organize and retrieve information in many domains, especially those dealing with large and rapidly growing amounts of information. In many of t...
Kunal Punera, Suju Rajan
148
Voted
ICDM
2003
IEEE
220views Data Mining» more  ICDM 2003»
15 years 9 months ago
Exploiting Unlabeled Data for Improving Accuracy of Predictive Data Mining
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
124
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CASCON
2001
148views Education» more  CASCON 2001»
15 years 5 months ago
Email classification with co-training
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
Svetlana Kiritchenko, Stan Matwin
153
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NIPS
2008
15 years 5 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