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Proceedings Paper

Detecting nonsense for Chinese comments based on logistic regression
Author(s): Ren Zhuolin; Chen Guang; Chen Shu
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Paper Abstract

To understand cyber citizens’ opinion accurately from Chinese news comments, the clear definition on nonsense is present, and a detection model based on logistic regression (LR) is proposed. The detection of nonsense can be treated as a binary-classification problem. Besides of traditional lexical features, we propose three kinds of features in terms of emotion, structure and relevance. By these features, we train an LR model and demonstrate its effect in understanding Chinese news comments. We find that each of proposed features can significantly promote the result. In our experiments, we achieve a prediction accuracy of 84.3% which improves the baseline 77.3% by 7%.

Paper Details

Date Published: 11 July 2016
PDF: 6 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 100111J (11 July 2016); doi: 10.1117/12.2242283
Show Author Affiliations
Ren Zhuolin, Beijing Univ. of Posts and Telecommunications (China)
Chen Guang, Beijing Univ. of Posts and Telecommunications (China)
Chen Shu, Beijing Univ. of Posts and Telecommunications (China)

Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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