A Part of Speech Based Public Opinion Text Classification Method

DOI

10.2991/ichssr-15.2015.46How to use a DOI?

Keywords

Public opinion; Text categorization; Part of speech; Feature extraction

Abstract

An improved text classification algorithm is presented to improve the accuracy and efficiency of the public opinion classification. The algorithm filters the part of speech before feature extraction to decrease the useless feature and then classifies text according to the calculated weight. The experimental results show that the feature extraction of the improved algorithm is more efficient than the previous ones, and the text classification results in different feature dimensions are more accurate, especially in the lower dimensions. Therefore, it has important significance for text classification by analyzing the weight of the part of speech to extract feature and calculate weight before classification.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Rui Liu
AU  - Zhiqiang Wei
AU  - Hao Liu
AU  - QianQian Fu
PY  - 2015/09
DA  - 2015/09
TI  - A Part of Speech Based Public Opinion Text Classification Method
BT  - Proceedings of the 2015 International Conference on Humanities and Social Science Research
PB  - Atlantis Press
SP  - 234
EP  - 238
SN  - 2352-5398
UR  - https://doi.org/10.2991/ichssr-15.2015.46
DO  - 10.2991/ichssr-15.2015.46
ID  - Liu2015/09
ER  -