@article{ART003090587},
author={Seoksoo Kim and Jae-Young Jung},
title={Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={6},
pages={13-22},
doi={10.9708/jksci.2024.29.06.013}
TY - JOUR
AU - Seoksoo Kim
AU - Jae-Young Jung
TI - Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 6
PB - The Korean Society Of Computer And Information
SP - 13
EP - 22
SN - 1598-849X
AB - There is a need for and positive aspects of article-based advertising, but as exaggerated and disguised information is delivered due to some indiscriminate 'article-based advertisements', readers have difficulty distinguishing between general articles and article-based advertisements, leading to a lot of misinterpretation and confusion of information. is doing Since readers will continue to acquire new information and apply this information at the right time and place to bring a lot of value, it is judged to be even more important to distinguish between accurate general articles and article-like advertisements. Therefore, as differentiated information between general articles and article-like advertisements is needed, as part of this, for readers who have difficulty identifying accurate information due to such indiscriminate article-like advertisements in Internet newspapers, this paper introduces IT and AI technologies. We attempted to present a method that can be solved in terms of a system that incorporates, and this method was designed to extract articleable advertisements using a knowledge-based natural language processing method that finds and refines advertising keywords and deep learning technology.
KW - Internet newspaper;article advertisement;deep learning;information extraction;media
DO - 10.9708/jksci.2024.29.06.013
ER -
Seoksoo Kim and Jae-Young Jung. (2024). Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning. Journal of The Korea Society of Computer and Information, 29(6), 13-22.
Seoksoo Kim and Jae-Young Jung. 2024, "Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning", Journal of The Korea Society of Computer and Information, vol.29, no.6 pp.13-22. Available from: doi:10.9708/jksci.2024.29.06.013
Seoksoo Kim, Jae-Young Jung "Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning" Journal of The Korea Society of Computer and Information 29.6 pp.13-22 (2024) : 13.
Seoksoo Kim, Jae-Young Jung. Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning. 2024; 29(6), 13-22. Available from: doi:10.9708/jksci.2024.29.06.013
Seoksoo Kim and Jae-Young Jung. "Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning" Journal of The Korea Society of Computer and Information 29, no.6 (2024) : 13-22.doi: 10.9708/jksci.2024.29.06.013
Seoksoo Kim; Jae-Young Jung. Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning. Journal of The Korea Society of Computer and Information, 29(6), 13-22. doi: 10.9708/jksci.2024.29.06.013
Seoksoo Kim; Jae-Young Jung. Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning. Journal of The Korea Society of Computer and Information. 2024; 29(6) 13-22. doi: 10.9708/jksci.2024.29.06.013
Seoksoo Kim, Jae-Young Jung. Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning. 2024; 29(6), 13-22. Available from: doi:10.9708/jksci.2024.29.06.013
Seoksoo Kim and Jae-Young Jung. "Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning" Journal of The Korea Society of Computer and Information 29, no.6 (2024) : 13-22.doi: 10.9708/jksci.2024.29.06.013
