딥러닝 기반의 소비자 데이터를 응용한 외식업체 추천 시스템 구현에 관한 연구

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 i...

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Bibliographic Details
Published inJournal of the convergence on culture technology : JCCT Vol. 7; no. 2; pp. 437 - 442
Main Authors 김희영, 정선미, 김우석, 류기환, 손현곤
Format Journal Article
LanguageKorean
Published 국제문화기술진흥원 31.05.2021
Subjects
과학기술학
Restaurant
분류
추천 시스템
Artificial Intelligence
Classification
딥러닝
외식업체
Recommendation System
Sentiment Analysis
인공지능
감성 분석
Deep Learning
Online AccessGet full text
ISSN2384-0358
2384-0366

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Summary: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
Bibliography:KISTI1.1003/JNL.JAKO202117242149803
http://ipact.kr/eng/bbs/board.php?bo_table=Recent_Issue_jcct&wr_id=37
ISSN:2384-0358
2384-0366