The Research of Chinese Short-text Classification Based on Domain Keyword Set Extension and HowNet

DOI

10.2991/icca-16.2016.57How to use a DOI?

Keywords

Short-text classification, Keyword set, LDA, Feature extension, HowNet

Abstract

To implement feature extension of short text and improve short text classification performance, this paper extracts the high frequency words and topic core words of each class of the training set as domain keyword set based on two different feature granularity, which are keyword and latent topic, and derives the topic probability distribution of the test text using LDA model, while some topic probability is greater than a certain threshold, extends the keywords of the topic into the testing text. Calculate the semantic similarity of the test text and the domain keyword set for each category by using HowNet. Experimental results show that the method proposed in this paper can effectively improve the short-text classification performance.

Copyright

© 2016, 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  - Xiangdong Li
AU  - Fan Gao
AU  - Cong Ding
PY  - 2016/01
DA  - 2016/01
TI  - The Research of Chinese Short-text Classification Based on Domain Keyword Set Extension and HowNet
BT  - Proceedings of the 2016 International Conference on Intelligent Control and Computer Application
PB  - Atlantis Press
SP  - 244
EP  - 247
SN  - 2352-538X
UR  - https://doi.org/10.2991/icca-16.2016.57
DO  - 10.2991/icca-16.2016.57
ID  - Li2016/01
ER  -