Chinese text classification based on neural network

Authors:
Hu Li;Peng Zou;WeiHong Han
Affiliations:
School of Computer, National University of Defense Technology, Changsha, Hunan Province, P.R. China;School of Computer, National University of Defense Technology, Changsha, Hunan Province, P.R. China;School of Computer, National University of Defense Technology, Changsha, Hunan Province, P.R. China
Venue:
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Year:
2013

Citing 9
Cited 0

What size net gives valid generalization?

Neural Computation
Neural Network Ensembles

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparative Study on Feature Selection in Text Categorization

ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Feature Reduction for Neural Network Based Text Categorization

DASFAA '99 Proceedings of the Sixth International Conference on Database Systems for Advanced Applications
Round robin classification

The Journal of Machine Learning Research
Neural Network for Text Classification Based on Singular Value Decomposition

CIT '07 Proceedings of the 7th IEEE International Conference on Computer and Information Technology
Text Categorization Using Neural Networks Initialized with Decision Trees

Informatica
Web Text Classification Using a Neural Network

EAIT '11 Proceedings of the 2011 Second International Conference on Emerging Applications of Information Technology
Analyzing document collections via context-aware term extraction

NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Text classification is widely used nowadays. In this paper, we proposed a combination feature reduction method to reduce feature space dimension based on inductive analysis of existing researches. Neural network was then trained and used to classify new documents. Existing researches mainly focus on the classification of the English text, but we focused on classification of Chinese text instead in this paper. Experimental results showed that the proposed feature reduction method performed well, and the neural network needed less terms to achieve the same accuracy compared with other classifiers.