Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Automated infographic recommendation system based on machine learning

기계학습 기반의 인포그래픽 자동 추천 시스템

  • 김형균 (국민대학교 소프트웨어학부) ;
  • 이상희 ((주)디자인스튜디오에이)
  • Received : 2021.08.17
  • Accepted : 2021.11.20
  • Published : 2021.11.28
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Abstract

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.

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.

Keywords

References

  1. M. S. Chung, S. H. Jeong & J. Y. Lee. (2018). Analysis of Major Research Trends in Artificial Intelligence Based on Domestic/international Patent Data. Journal of Digital Convergence, 16(6), 187-195. DOI : 10.14400/JDC.2018.16.6.187
  2. M. S. Chung, H. H. Jeong, U. Chae, G. H. Lee & J. Y. Lee. (2017). A Study On Technical Trend Analysis Related to Semantic Analysis of NLP Through Domestic/Foreign Patent Data. Journal of Digital Convergence, 18(1), 137-146. DOI : 10.14400/JDC.2020.18.1.137
  3. M. S. Chung, S. H. Park, B. H. Chae & J. Y. Lee. (2017). Analysis of Major Research Trends in Artificial Intelligence through Analysis of Thesis Data. Journal of Digital Convergence, 15(5), 225-233. DOI : 10.14400/JDC.2017.15.5.225
  4. M. Farboodi, R. Mihet, T. Philippon & L. Veldkamp. (2019). Big Data and Firm Dynamics. National Bur eau of Economic Research Working Papers 25515.
  5. S. Ahtey, D. Blei, R. Donnelly, F. Ruiz & T. Schmidt. (2018). Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data. In AEA Papers and Proceedings, 108, 64-67. https://doi.org/10.1257/pandp.20181031
  6. R. Evans & J. Gao. (2016). Deepmind AI Reduces Google Data Centre Cooling Bill by 40%. DeepMind blog 20. https://deepmind.com/blog/article/deepmin d-ai-reduces-google-data-centre-cooling-bill-40
  7. H. S. Lee et al. (2020.7.28.) LG, Automating Production in Secondary Partners Using AI and Big-Data. Maeil Business Newspaper . https://www.mk.co.kr/news/special-edition/view/2020/07/768385/
  8. S. S. Lee, L. H. Yoo & J. H. KIM. (2020). An Analysis of Public Perception on Artificial Intelligence (AI) Education Using Big Data: Based on News Articles and Twitter. Journal of Digital Convergence, 18(6), 9-16. DOI : 10.14400/JDC.2020.18.6.009
  9. H. J. Han, K. J. Kim & H. S. Kwon. (2020). The Analysis of Elementary School Teachers' Perception of Using Artificial Intelligence in Education. Journal of Digital Convergence, 18(7), 47-56. DOI : 10.14400/JDC.2020.18.7.047
  10. Smiciklas, M. The Power of Infographics: Using Pictures to Communicate and Connect with your Audiences. Indianapolis. IN: Que Publishing, 2012.
  11. H. J. Lee, Y. S. Bae, M. J. Son, Information Design, Seoul: Gyomunsa. 2011. p. 27.
  12. Peterson, B. K, "Tables and Graphics Improve Reader Performance and Reader Reaction", Journal of Business Communication, Vol. 20, pp. 47-55, 1983. https://doi.org/10.1177/002194368302000204
  13. Plass, J. L., Chun, D. M., Mayer, R. E., & Leutner, D. "Cognitive Load in Reading a Foreign Language Text with Multimedia Aids and The Influence of Verbal and spatial Abilities", Computers in Human Behavior, Vol. 19, pp. 221-243, 2003. https://doi.org/10.1016/S0747-5632(02)00015-8
  14. S. Hwang & Y. J. Nam. (2020). The Role of Confidence in Government in Acceptance Intention towards Artificial Intelligence. Journal of Digital Convergence, 18(8), 217-224. DOI : 10.14400/JDC.2020.18.8.217
  15. F. Cady. (2017). The data science handbook. Wiley.
  16. S. Kim & Y. Jeong. (2017). Machine Learning. Seoul : Hanbit Media.