@article{ART002719121},
author={Young-Dan Noh and Kyu-Cheol Cho},
title={A Text Content Classification Using LSTM For Objective Category Classification},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2021},
volume={26},
number={5},
pages={39-46},
doi={10.9708/jksci.2021.26.05.039}
TY - JOUR
AU - Young-Dan Noh
AU - Kyu-Cheol Cho
TI - A Text Content Classification Using LSTM For Objective Category Classification
JO - Journal of The Korea Society of Computer and Information
PY - 2021
VL - 26
IS - 5
PB - The Korean Society Of Computer And Information
SP - 39
EP - 46
SN - 1598-849X
AB - AI is deeply applied to various algorithms that assists us, not only daily technologies like translator and Face ID, but also contributing to innumerable fields in industry, due to its dominance. In this research, we provide convenience through AI categorization, extracting the only data that users need, with objective classification, rather than verifying all data to find from the internet, where exists an immense number of contents. In this research, we propose a model using LSTM(Long-Short Term Memory Network), which stands out from text classification, and compare its performance with models of RNN(Recurrent Neural Network) and BiLSTM(Bidirectional LSTM), which is suitable structure for natural language processing. The performance of the three models is compared using measurements of accuracy, precision, and recall. As a result, the LSTM model appears to have the best performance.
Therefore, in this research, text classification using LSTM is recommended.
KW - AI;contents;categorization;LSTM;natural language
DO - 10.9708/jksci.2021.26.05.039
ER -
Young-Dan Noh and Kyu-Cheol Cho. (2021). A Text Content Classification Using LSTM For Objective Category Classification. Journal of The Korea Society of Computer and Information, 26(5), 39-46.
Young-Dan Noh and Kyu-Cheol Cho. 2021, "A Text Content Classification Using LSTM For Objective Category Classification", Journal of The Korea Society of Computer and Information, vol.26, no.5 pp.39-46. Available from: doi:10.9708/jksci.2021.26.05.039
Young-Dan Noh, Kyu-Cheol Cho "A Text Content Classification Using LSTM For Objective Category Classification" Journal of The Korea Society of Computer and Information 26.5 pp.39-46 (2021) : 39.
Young-Dan Noh, Kyu-Cheol Cho. A Text Content Classification Using LSTM For Objective Category Classification. 2021; 26(5), 39-46. Available from: doi:10.9708/jksci.2021.26.05.039
Young-Dan Noh and Kyu-Cheol Cho. "A Text Content Classification Using LSTM For Objective Category Classification" Journal of The Korea Society of Computer and Information 26, no.5 (2021) : 39-46.doi: 10.9708/jksci.2021.26.05.039
Young-Dan Noh; Kyu-Cheol Cho. A Text Content Classification Using LSTM For Objective Category Classification. Journal of The Korea Society of Computer and Information, 26(5), 39-46. doi: 10.9708/jksci.2021.26.05.039
Young-Dan Noh; Kyu-Cheol Cho. A Text Content Classification Using LSTM For Objective Category Classification. Journal of The Korea Society of Computer and Information. 2021; 26(5) 39-46. doi: 10.9708/jksci.2021.26.05.039
Young-Dan Noh, Kyu-Cheol Cho. A Text Content Classification Using LSTM For Objective Category Classification. 2021; 26(5), 39-46. Available from: doi:10.9708/jksci.2021.26.05.039
Young-Dan Noh and Kyu-Cheol Cho. "A Text Content Classification Using LSTM For Objective Category Classification" Journal of The Korea Society of Computer and Information 26, no.5 (2021) : 39-46.doi: 10.9708/jksci.2021.26.05.039
