Earticle

초록

영어

Tourism is considered as one of the most important industries in Vietnam. The Government continuously keeps managing and asking for improving all sectors related to tourism. As an important infrastructure for tourism industries, hotels for accommodation are highly considered for improving customer services. On hotel booking and reviews channels, customers express their opinions and feedback about their experienced hotels by writing online reviews, this is valuable source of information that hotel managers should utilize. In this study, we collected 37,712 online reviews about Vietnamese hotels written by domestic and foreign customers in Vietnamese and English languages. Then we developed a hybrid model to perform opinion mining on multilingual social media text and explore for customer opinion differences across cultures. The results show that there are differences in hotel service preferences between Vietnamese and American customers. Based on this research result we recommend for improving customer satisfactions via diversifying across cultures services.

목차

Abstract
 1. Introduction
 2. Literature Review
  2.1. Text mining
  2.2. Opinion mining
  2.3. Opinion mining techniques
  2.4. Vietnamese text mining
 3. Research methods
  3.1. Data Collection
  3.2. Data preprocessing
  3.3. Lexicon-based model design
  3.4. Machine learning model design
  3.5. Hybrid model design
 4. Experiment results
  4.1. Lexicon-based opinion mining results
  4.2. Machine learning based and hybrid model results
  4.3. Application of opinion mining in hotel services industry
  4.4. Discussions
 5. Conclusions
 References

키워드

저자

• Hoanh-Su Le [ Candidate Ph. D., Graduate School of Business, Pukyong National University, S. Korea ]
• Jong-Hwa Lee [ Candidate Ph. D., Graduate School of Business, Pukyong National University, S. Korea ]
• Hyun-Kyu Lee [ Candidate Ph. D., Graduate School of Business, Pukyong National University, S. Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658