디지털융복합연구 (Journal of Digital Convergence)

한국디지털정책학회 (The Society of Digital Policy and Management)
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기계학습 기반의 인포그래픽 자동 추천 시스템

Automated infographic recommendation system based on machine learning

  • 김형균 (국민대학교 소프트웨어학부) ;
  • 이상희 ((주)디자인스튜디오에이)
  • 투고 : 2021.08.17
  • 심사 : 2021.11.20
  • 발행 : 2021.11.28
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초록

본 논문에서는 기존의 인포그래픽 제작방식을 개선하기 위하여 기계학습 기반의 인포그래픽 자동 추천 시스템을 제안하였다. 이 시스템은 복수의 인포그래픽 이미지를 기계학습하는 부분과 사용자의 기초자료 입력만으로 인포그래픽을 인공지능으로 자동 추천하는 부분으로 구성된다. 추천된 인포그랙픽은 라이브러리 형태로 제공되고, 드래그 & 드롭방식으로 추가적인 자료의 입력이 가능하게 된다. 또한, 입력한 자료의 크기에 따라 인포그래픽 이미지가 동적으로 조절되도록 설계하였다. 기계학습 기반의 인포그래픽 자동 추천 과정을 분석한 결과 레이아웃과 키워드에 대한 일치 성공율은 매우 높고, 타입에 대한 일치 성공률은 다소 낮게 나타났다. 추후 인포그래픽 부분별 이미지 타입에 대한 일치 성공률을 향상시키기 위한 연구가 필요할 것이다.

In this paper, a machine learning-based automatic infographic recommendation system is proposed to improve the existing infographic production method. This system consists of a part that machine learning multiple infographic images and a part that automatically recommends infographics with artificial intelligence only by inputting basic data from the user. The recommended infographics are provided in the form of a library, and additional data can be input by drag & drop method. In addition, the infographic image is designed to be dynamically adjusted according to the size of the input data. As a result of analyzing the machine learning-based automatic infographic recommendation process, the matching success rate for layout and keyword was very high, and the matching success rate for type was rather low. In the future, a study to improve the matching success rate for the image type for each part of the infographic will be needed.

키워드

참고문헌

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