Sentiment analysis can be applied to all texts generated from websites, blogs, messengers, etc. The study fulfills an artificial intelligence sentiment analysis estimating visiting evaluation opinions (reviews) and visitor ratings, and suggests a deep learning model which foretells either an affirmative or a negative inclination for new reviews. This study operates review big data about Jeju tourist attractions which are extracted from Google from October 1st, 2021 to November 30th, 2021. The normalization data used in the propensity prediction modeling of this study were divided into training data and test data at a 7.5:2.5 ratio, and the CNN classification neural network was used for learning. The predictive model of the research indicates an accuracy of approximately 84.72%, which shows that it can upgrade performance in the future as evaluating its error rate and learning precision.
목차
Abstract 1. INTRODUCTION 2. RELATED WORKS 2.1 Opinion Mining and Sentiment Analysis 2.2 Natural language processing(NLP) and ChatGPT 2.3 Deep Learning & CNN 3. PROPOSED METHOLOGY AND PREDICTION MODEL 3.1 Deep Learning Overview 3.2 Data Normalization and Preprocessing 3.3 Creating a Sentiment Analysis Model 4. RESULT OF EXPERIMENT AND DISCUSSION 5. CONCLUSION REFERENCES
국제문화기술진흥원 [The International Promotion Agency of Culture Technology]
설립연도
2009
분야
공학>공학일반
소개
본 진흥원은 문화기술(Culture Technology) 관련 산·학·연·관으로 구성된 비영리 단체이다. 문화기술(CT)은 정보통신기술(ICT), 문화적 사고 기반의 예술, 인문학, 디자인, 사회과학기술이 접목된 신융합기술(New Convergence Technology, NCT)로 정의한다. 인간의 삶의 질을 향상시키고, 진보된 방향으로 변화시키고, 문화기술 관련 분야의 학술 및 기술의 발전과 진흥에 공헌하기 위하여, 제3조의 필요한 사업을 행함을 그 목적으로 한다.
간행물
간행물명
International Journal of Advanced Culture Technology(IJACT)
간기
계간
pISSN
2288-7202
eISSN
2288-7318
수록기간
2013~2025
등재여부
KCI 등재
십진분류
KDC 600DDC 700
이 권호 내 다른 논문 / International Journal of Advanced Culture Technology(IJACT) Volume 11 Number 3