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[국내논문] A Study on the Restaurant Recommendation Service App Based on AI Chatbot Using Personalization Information 원문보기

The International journal of advanced culture technology, v.8 no.4, 2020년, pp.263 - 270  

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)

Abstract ▼ AI-Helper 아이콘AI-Helper

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 informati...

주제어

#personalization information   #AI chatbot   #restaurant recommendation service app   #collaborative filtering  

표/그림 (5)

AI 본문요약
AI-Helper 아이콘 AI-Helper

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제안 방법

  • In addition, the system was constructed for the recommended application of the restaurant based on artificial intelligence chatbot, which utilized the proposed personalization information. This is based on Chat System with Collaborative Filtering System, User Interface, personalization information, and database containing realtime information.
  • So, user1 is recommended item 3 of User 2 which has not been experienced to user1. In this study, we propose a recommendation service app design using personalization information and collaborative filtering techniques in recommending restaurant.

이론/모형

  • The methods of personalization include the Rules-based filtering method, the leading agent method, and the collaborative filtration method [5]. In this study, the process of deriving personalization information is used to enhance the satisfaction of recommendation by using the collaborative filtering method.
본문요약 정보가 도움이 되었나요?

참고문헌 (13)

  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 

    상세보기 crossref

  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 

    상세보기 crossref

  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 

    상세보기 crossref

  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. 

    원문보기 상세보기 crossref

  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. 

    원문보기 상세보기 crossref

  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 

    원문보기 상세보기 crossref

  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. 

    crossref

  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. 

    crossref

  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 

    원문보기 상세보기 crossref

  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. 

    원문보기 상세보기 crossref

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