@article{ART002987872},
author={Kil-Sang Yoo and Jin-Hee Jang and Seong-Ju Kim and Gwang-Yong Gim},
title={A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2023},
volume={28},
number={8},
pages={21-30},
doi={10.9708/jksci.2023.28.08.021}
TY - JOUR
AU - Kil-Sang Yoo
AU - Jin-Hee Jang
AU - Seong-Ju Kim
AU - Gwang-Yong Gim
TI - A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet
JO - Journal of The Korea Society of Computer and Information
PY - 2023
VL - 28
IS - 8
PB - The Korean Society Of Computer And Information
SP - 21
EP - 30
SN - 1598-849X
AB - The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.
KW - Illegal Financial Advertisements;Deep Learning;CNN;RNN;LSTM;GRU
DO - 10.9708/jksci.2023.28.08.021
ER -
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim and Gwang-Yong Gim. (2023). A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet. Journal of The Korea Society of Computer and Information, 28(8), 21-30.
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim and Gwang-Yong Gim. 2023, "A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet", Journal of The Korea Society of Computer and Information, vol.28, no.8 pp.21-30. Available from: doi:10.9708/jksci.2023.28.08.021
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim, Gwang-Yong Gim "A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet" Journal of The Korea Society of Computer and Information 28.8 pp.21-30 (2023) : 21.
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim, Gwang-Yong Gim. A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet. 2023; 28(8), 21-30. Available from: doi:10.9708/jksci.2023.28.08.021
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim and Gwang-Yong Gim. "A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet" Journal of The Korea Society of Computer and Information 28, no.8 (2023) : 21-30.doi: 10.9708/jksci.2023.28.08.021
Kil-Sang Yoo; Jin-Hee Jang; Seong-Ju Kim; Gwang-Yong Gim. A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet. Journal of The Korea Society of Computer and Information, 28(8), 21-30. doi: 10.9708/jksci.2023.28.08.021
Kil-Sang Yoo; Jin-Hee Jang; Seong-Ju Kim; Gwang-Yong Gim. A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet. Journal of The Korea Society of Computer and Information. 2023; 28(8) 21-30. doi: 10.9708/jksci.2023.28.08.021
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim, Gwang-Yong Gim. A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet. 2023; 28(8), 21-30. Available from: doi:10.9708/jksci.2023.28.08.021
Kil-Sang Yoo, Jin-Hee Jang, Seong-Ju Kim and Gwang-Yong Gim. "A Study on Deep Learning Model for Discrimination of Illegal Financial Advertisements on the Internet" Journal of The Korea Society of Computer and Information 28, no.8 (2023) : 21-30.doi: 10.9708/jksci.2023.28.08.021
