A HowNet-based feature selection method for Chinese text representation

Authors:
Changwei Zhao;Xueli Yao;Suhuan Sun
Affiliations:
School of Electronic and Information Engineering, Henan University of Science & Technology, Luoyang, China;Henan Administrative, Institute of Politics and Law, Zhengzhou, China;School of Electronic and Information Engineering, Henan University of Science & Technology, Luoyang, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Year:
2009

Citing 4
Cited 0

A re-examination of text categorization methods

Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing

Communications of the ACM
A Comparative Study on Feature Selection in Text Categorization

ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Measuring the semantic similarity of texts

EMSEE '05 Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment

Quantified Score

Hi-index	0.00

Visualization

Abstract

Data dimension reduction plays an important role in the field of text representation. An effective dimension reduction method can not only reduce computation complexity, but help to improve the accuracy of text classification. This paper presents a new method of dimension reduction which is based on words semantic similarities. Being different with traditional methods which usually use the statistical information of words, natural language processing knowledge is used in our method which considers semantic information and POS information of feature terms. The experimental results show that our method is effective in dimensionality reduction of text representation and achieves a higher accuracy of text classification. The semantic similarity based method is a suitable method for text representation.