Building a Text Classifier by a Keyword and Wikipedia Knowledge
Authors | Qiang Qiu Yang Zhang Junping Zhu Wei Qu |
|---|---|
Publication date | 2009 |
DOI | 10.1007/978-3-642-03348-3_28 |
Links | Original |
Building a Text Classifier by a Keyword and Wikipedia Knowledge - scientific work related to Wikipedia quality published in 2009, written by Qiang Qiu, Yang Zhang, Junping Zhu and Wei Qu.
Overview
Traditional approach for building text classifiers usually require a lot of labeled documents, which are expensive to obtain. In this paper, authors propose a new text classification approach based on a keyword and Wikipedia knowledge, so as to avoid labeling documents manually. Firstly, authors 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, authors 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.
Embed
Wikipedia Quality
Qiu, Qiang; Zhang, Yang; Zhu, Junping; Qu, Wei. (2009). "[[Building a Text Classifier by a Keyword and Wikipedia Knowledge]]". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-03348-3_28.
English Wikipedia
{{cite journal |last1=Qiu |first1=Qiang |last2=Zhang |first2=Yang |last3=Zhu |first3=Junping |last4=Qu |first4=Wei |title=Building a Text Classifier by a Keyword and Wikipedia Knowledge |date=2009 |doi=10.1007/978-3-642-03348-3_28 |url=https://wikipediaquality.com/wiki/Building_a_Text_Classifier_by_a_Keyword_and_Wikipedia_Knowledge |journal=Springer, Berlin, Heidelberg}}
HTML
Qiu, Qiang; Zhang, Yang; Zhu, Junping; Qu, Wei. (2009). "<a href="https://wikipediaquality.com/wiki/Building_a_Text_Classifier_by_a_Keyword_and_Wikipedia_Knowledge">Building a Text Classifier by a Keyword and Wikipedia Knowledge</a>". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-03348-3_28.
