ChatGPT와 딥러닝 알고리즘의 기능 비교

• 영문명: A Comparison of ChatGPT and Deep Learning Algorithm: Recommendation System for Tourism and Cafe
• 발행기관: 한국커피협회
• 저자명: 양오석 신승렬
• 간행물 정보: 『한국커피문화연구』제9권 1호, 77~108쪽, 전체 32쪽
• 주제분류: 복합학 > 학제간연구
• 파일형태: PDF
• 발행일자: 2023.06.30

영문 초록

As a heuristic approach for comparative analysis, the functions of ChatGPT and deep learning recommendation algorithm were examined through the case of Chuncheon tourist destination and cafe recommendation system. As a result of the study, it was found that ChatGPT's recommendation system is not a preference-based personalized method that identifies individual preferences and tastes and recommends corresponding content, but a sequential method that provides information on the characteristics of various types of content and allows users to make final choices. In contrast, the deep learning recommendation algorithm is a personalized recommendation system that first learns information about individual preferences and tastes and recommends content applying a user-based or item-based algorithm. As a result, it can be said that ChatGPT values ​​diversity of content from the perspective of providing balanced information that emphasizes generality, and deep learning recommendation algorithm values ​​personalized service that emphasizes specificity.

목차

Ⅰ. 서론

Ⅱ. 주요 개념 및 이론적 배경

Ⅲ. 연구 방법 및 분석 결과

Ⅳ. 결론

참고문헌

키워드

Cafe Tourism ChatGPT Recommendation Algorithm Deep Learning