Junping Zhu

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Junping Zhu is an author.


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Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Building a text classifier by a keyword and Wikipedia knowledge Keyword
Text classification
Unlabeled document
Lecture Notes in Computer Science English 2009 Traditional approach for building text classifiers usually require a lot of labeled documents, which are expensive to obtain. In this paper, we propose a new text classification approach based on a keyword and Wikipedia knowledge, so as to avoid labeling documents manually. Firstly, we retrieve a set of related documents about the keyword from Wikipedia. And then, with the help of related Wikipedia pages, more positive documents are extracted from the unlabeled documents. Finally, we train a text classifier with these positive documents and unlabeled documents. The experiment result on 20Newsgroup dataset show that the proposed approach performs very competitively compared with NB-SVM, a PU learner, and NB, a supervised learner. 0 0