A Kind of Text Classification Method Based on Fuzzy Vector Space Model and Neural Networks

DOI

10.2991/iccsee.2013.492How to use a DOI?

Keywords

Text classification, fuzzy vector space, neural networks, fuzzy feature vector, feature extracted, membership

Abstract

A kind of text classification method based on fuzzy vector space model and neural networks is proposed in the paper according to the problems that a text can be belongs to many types during the text classification. Fuzzy theory is adopted in the method to look the occurring position of feature items in text on as the important degree (membership) reflecting text subject, and fully considered the position information while the features are extracted, thus the fuzzy feature vectors are constructed, as a result, the text classification is close to the manual classification method. The established networks are constituted of input layer, hidden layer and output layer, the input layer completes the inputs of classification samples, hidden layer extracts the implicit pattern features of input samples, the output layer is used to output the classification results. Finally the effectiveness of this method is proved by some documents of Wan Fang data in experimental section.

Copyright

© 2013, 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  - JunHui PAN
AU  - Hui LI
PY  - 2013/03
DA  - 2013/03
TI  - A Kind of Text Classification Method Based on Fuzzy Vector Space Model and Neural Networks
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 1959
EP  - 1961
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.492
DO  - 10.2991/iccsee.2013.492
ID  - PAN2013/03
ER  -