Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning (기사성광고 분석 및 딥러닝을 활용한 기사성광고 추출 방법 설계에 관한 연구)

Seoksoo Kim (김석수); Jung, Jae-Young (정재영)

doi:10.9708/jksci.2024.29.06.013

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
Abbr : JKSCI
2024, 29(6), pp.13~22
DOI : 10.9708/jksci.2024.29.06.013
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : May 7, 2024
Accepted : June 3, 2024
Published : June 28, 2024

Seoksoo Kim ¹, Jung, Jae-Young ²

¹한남대학교
²동양대학교

Accredited

ABSTRACT

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.

KEYWORDS

Internet newspaper, article advertisement, deep learning, information extraction, media

Citation status

* References for papers published after 2024 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

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Journal of The Korea Society of Computer and Information 2024 KCI Impact Factor : 0.81

Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning

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* References for papers published after 2024 are currently being built.

Journal of The Korea Society of Computer and Information 2024 KCI Impact Factor : 0.81

Research on analysis of articleable advertisements and design of extraction method for articleable advertisements using deep learning

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KEYWORDS

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* References for papers published after 2024 are currently being built.