The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Study on Implementation of Restaurant Recommendation System based on Deep Learning-based Consumer Data

딥러닝 기반의 소비자 데이터를 응용한 외식업체 추천 시스템 구현에 관한 연구

  • 김희영 (광운대학교 대학원 실감융합콘텐츠학과) ;
  • 정선미 (광운대학교 대학원 실감융합콘텐츠학과) ;
  • 김우석 (광운대학교 대학원 전자재료공학과) ;
  • 류기환 (광운대학교 스마트융합대학원) ;
  • 손현곤 (광운대학교 대학원 실감융합콘텐츠학과)
  • Received : 2021.04.20
  • Accepted : 2021.05.07
  • Published : 2021.05.31
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Abstract

In this study, a recommendation algorithm was implemented by learning a deep learning-based classification model for consumer data. For this purpose, a meaningful result is presented as a result of learning using ResNet50, which is commonly used in classification tasks by converting user data into images.

본 연구에서는 소비자 데이터를 딥러닝 기반의 분류(Classification) 모델을 학습 시켜 추천 알고리즘을 구현하였다. 이를 위하여 사용자 데이터를 이미지로 변환 시켜 분류 과제에서 보편적으로 사용되는 ResNet50을 사용하여 학습한 결과로서 유의미한 결과에 대하여 제시함

Keywords

References

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