International Journal of Advanced Culture Technology

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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A Study on the Restaurant Recommendation Service App Based on AI Chatbot Using Personalization Information

  • Kim, Heeyoung (Department of Immersive Content Convergence, General graduate school, Kwangwoon University) ;
  • Jung, Sunmi (Department of Tourism Industry, Graduate school of smart convergence, Kwangwoon University) ;
  • Ryu, Gihwan (Department of Immersive Content Convergence, General graduate school, Kwangwoon University)
  • Received : 2020.10.30
  • Accepted : 2020.12.11
  • Published : 2020.12.31
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Abstract

The growth of the mobile app markets has made it popular among people who recommend relevant information about restaurants. The recommendation service app based on AI Chatbot is that it can efficiently manage time and finances by making it easy for restaurant consumers to easily access the information they want anytime, anywhere. Eating out consumers use smartphone applications for finding restaurants, making reservations, and getting reviews and how to use them. In addition, social attention has recently been focused on the research of AI chatbot. The Chatbot is combined with the mobile messenger platform and enabling various services due to the text-type interactive service. It also helps users to find the services and data that they need information tersely. Applying this to restaurant recommendation services will increase the reliability of the information in providing personal information. In this paper, an artificial intelligence chatbot-based smartphone restaurant recommendation app using personalization information is proposed. The recommendation service app utilizes personalization information such as gender, age, interests, occupation, search records, visit records, wish lists, reviews, and real-time location information. Users can get recommendations for restaurants that fir their purpose through chatting using AI chatbot. Furthermore, it is possible to check real-time information about restaurants, make reservations, and write reviews. The proposed app uses a collaborative filtering recommendation system, and users receive information on dining out using artificial intelligence chatbots. Through chatbots, users can receive customized services using personal information while minimizing time and space limitations.

Keywords

References

  1. M.J. Kim, "The Intention to Provide Personal Information among Location-Based Matjib App Service Users: A Privacy Calculus Perspective", International Journal of Tourism Management and Sciences (KASTM), Vol. 33, No. 6, pp. 1-21, September 2018. DOI: 10.21719/IJTMS.33.6.1
  2. S.O. Yoon, "Issues of Public Service Using Artificial Intelligence: Focused on Chatbot Service", Korean Public Management Review, Vol. 32, No. 2, pp. 83-104, June 2018. DOI: 10.24210/kapm.201 8.32.2.004
  3. S.H. Byun, C.H. Cho, "The Effect of the Anthropomorphism Level and Personalization Level on AI Financial Chatbot Recommendation Messages on Customer Response", The Korean Journal of Advertising and Public Relations (KADPR), Vol. 22, No. 2, pp. 466-502, April 2020. DOI: 10.16914/kadpr.2020.22.2.466
  4. Y. Kim, "A Study on Design and Implementation of Personalized Information Recommendation System based on Apriori Algorithm", Journal of the Korean Biblia Society for Library and Information Science, Vol. 23, No. 4, pp. 283-308, December 2012. https://doi.org/10.14699/kbiblia.2012.23.4.283
  5. Y.S. Kim, "Research Trend of Recommendation System for Personalization Service", Industrial Engineering Magazine, Vol. 19, No. 1, pp. 37-42, March 2020.
  6. A.R. Park, S.B. Lee, and J.M. Song, "Application of AI based Chatbot Technology in the Industry", Journal of the Korea Society of Computer and Information, Vol. 25, No. 7, pp. 17-25, July 2020. https://doi.org/10.9708/JKSCI.2020.25.07.017
  7. H.N. Yoo, J.Y. Choi, S.G. Han, and J.U. Park, "Dialog map and guidelines for conversational user interface design of chatbot", in Proc. Journal of the HCI Society of Korea, pp. 86-91, January 2018.
  8. M.J. Kang, "A Study of Chatbot Personality based on the Purposes of Chatbot", The Journal of the Korea Contents Association, Vol. 18, No. 5, pp. 319-329, May 2018. DOI: 10.5392/JKCA.2018.18.05.319
  9. J.S. Han, "A Study on Effects of the Service Quality and the Usage Review Characteristics of Smartphone Majib App on Satisfaction and Reuse Intention of Majib App", Culinary Science & Hospitality Research, Vol. 22, No. 2, pp. 234-251, February 2016. https://doi.org/10.20878/cshr.2016.22.2.019019
  10. K.J. Kim, B.S. Lee, "The Exploratory Study on the Easiness of Using Smart Phone Applications for Searching Food Service Information: Focusing on Consumer Characteristics", Culinary Science & Hospitality Research, Vol. 17, No. 5, pp. 108-121, December,2011. https://doi.org/10.20878/cshr.2011.17.5.008
  11. H.M. Yun, K.W. Choi, "A research of food menu recommendation system based on personal preference", Korean Journal of Hospitality and Tourism (KJHT), Vol. 29, No. 1, pp. 83-100, January 2016. DOI: 10.24992/KJHT.2020.01.29.01.83
  12. J.E. Son, S.B. Kim, H.J. Kim, and S.Z. Cho, "Review and Analysis of Recommender Systems", Journal of the Korean Institute of Industrial Engineers, Vol. 41, No. 2, pp. 185-208, April 2015. DOI: 10.7232/JKIIE.2015.41.2.185
  13. J. Byun, D.K. Kim, "Design and Implementation of Location Recommending Services using Personal Emotional Information based on Collaborative Filtering", Journal of Korea Institute of Information and Communication Engineering (JKIICE), Vol. 20, No. 8, pp. 1407-1414, August 2016. https://doi.org/10.6109/jkiice.2016.20.8.1407