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» Combining feature selectors for text classification
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MLDM
2007
Springer
14 years 1 months ago
PE-PUC: A Graph Based PU-Learning Approach for Text Classification
This paper presents a novel solution for the problem of building text classifier using positive documents (P) and unlabeled documents (U). Here, the unlabeled documents are mixed w...
Shuang Yu, Chunping Li
IJCAI
2003
13 years 8 months ago
Learning to Classify Texts Using Positive and Unlabeled Data
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
Xiaoli Li, Bing Liu
AAAI
2004
13 years 9 months ago
Text Classification by Labeling Words
Traditionally, text classifiers are built from labeled training examples. Labeling is usually done manually by human experts (or the users), which is a labor intensive and time co...
Bing Liu, Xiaoli Li, Wee Sun Lee, Philip S. Yu
BMCBI
2005
134views more  BMCBI 2005»
13 years 7 months ago
Systematic feature evaluation for gene name recognition
In task 1A of the BioCreAtIvE evaluation, systems had to be devised that recognize words and phrases forming gene or protein names in natural language sentences. We approach this ...
Jörg Hakenberg, Steffen Bickel, Conrad Plake,...
IJCNLP
2004
Springer
14 years 25 days ago
A Study of Semi-discrete Matrix Decomposition for LSI in Automated Text Categorization
Abstract. This paper proposes the use of Latent Semantic Indexing (LSI) techniques, decomposed with semi-discrete matrix decomposition (SDD) method, for text categorization. The SD...
Qiang Wang, Xiaolong Wang, Guan Yi