skip to main content
10.1145/3342428.3342664acmotherconferencesArticle/Chapter ViewAbstractPublication PagesgoodtechsConference Proceedingsconference-collections
research-article

Design and implementation of an airport chatbot

Published:25 September 2019Publication History

ABSTRACT

In the era of universal digitalization and always-connected consumers, companies are expected to offer pervasive, uninterrupted and friendly customer care services. To this end, the recent advances in natural language understanding, enable the creation of artificial attendants, called "chatbots", that were once confined within the domain of science-fiction. This work discusses the design and implementation of a customer support chatbot for the Venice Airport. The main goal of the research was to design a common core able to interact 24/7 by means different paradigms, ranging from speech to touch screens, and through different user interfaces, including mobile phones, fixed installations and physical robots roaming the terminal. This goal has been reached by exploiting modern cloud-based services and by designing a specially-crafted modular system able to interface itself with both online information providers and legacy data sources supplied by the airport ICT infrastructure. This work describes the engineering process, from the prerequisites analysis to a functional description of the devised architecture, and the implementation details of the system presenting a working prototype of the airport chatbot.

References

  1. Aeromexico. 2017. Aeromexico chatbot. https://www.passengerselfservice.com/2017/04/aeromexico-to-expand-use-of-its-aerobot-chatbot/.Google ScholarGoogle Scholar
  2. Airport AI. 2019. Official Website. https://www.airport.ai/.Google ScholarGoogle Scholar
  3. M. Carisi. 2019. Design and implementation of a chatbot for Marco Polo Airport of Venice. Master's thesis. Università Ca' Foscari, Venezia.Google ScholarGoogle Scholar
  4. V. Chattaraman, W. Kwon, and J.E. Gilbert. 2012. Virtual agents in retail web sites: Benefits of simulated social interaction for older users. Computers in Human Behavior 28, 6 (2012), 2055--2066. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. E. Choi, E. Ko, and A.J. Kim. 2016. Explaining and predicting purchase intentions following luxury-fashion brand value co-creation encounters. Jour. of Business Research 69, 12 (2016), 5827--5832.Google ScholarGoogle ScholarCross RefCross Ref
  6. K. Chung and R.C. Park. 2017. Cloud based u-healthcare network with QoS guarantee for mobile health service. Cluster Computing (24 Oct 2017).Google ScholarGoogle Scholar
  7. M. Chung, E. Ko, H. Joung, and S.J. Kim. 2018. Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research (2018).Google ScholarGoogle Scholar
  8. L. Cui, S. Huang, F. Wei, C. Tan, C. Duan, and M. Zhou. 2017. SuperAgent: A Customer Service Chatbot for E-commerce Websites. In Proceedings of ACL 2017, System Demonstrations.Google ScholarGoogle Scholar
  9. Fraport. 2017. FRAnky. https://www.fraport.com/content/fraport/en/our-company/media/newsroom/service-news/2017/frankfurt-airport-offers-new-digital-services.html.Google ScholarGoogle Scholar
  10. U. Gnewuch, S. Morana, and A. Maedche. 2017. Towards Designing Cooperative and Social Conversational Agents for Customer Service. In Proceedings of the 38th International Conference on Information Systems (ICIS).Google ScholarGoogle Scholar
  11. E. Gregori. 2017. Evaluation of Modern Tools for an OMSCS Advisor Chatbot, Georgia Institute of Technology (Ed.).Google ScholarGoogle Scholar
  12. K. Hassanein and M. Head. 2007. Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping. International Journal of Human-Computer Studies 65, 8 (2007), 689--708. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J. Jia. 2004. CSIEC(Computer Simulator in Educational Communication): An Intelligent Web-Based Teaching System for Foreign Language Learning. In Proceedings of EdMedia + Innovate Learning 2004. AACE, 4147--4152.Google ScholarGoogle Scholar
  14. D.A. Kane. 2016. The Role of Chatbots in Teaching and Learning. E-Learning and the Academic Library: Essays on Innovative Initiatives. Location: McFarland. UC Irvine: Libraries. (2016).Google ScholarGoogle Scholar
  15. A. Kerly, P. Hall, and S. Bull. 2007. Bringing Chatbots into education: Towards Natural Language Negotiation of Open Learner Models. Knowledge-Based Systems 20 (03 2007), 177--185. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. C. Kuhlthau. 1994. Students and the Information Search Process: Zones of Intervention for Librarians. Advances in Librarianship 18 (1994), 57--72.Google ScholarGoogle ScholarCross RefCross Ref
  17. C. Kuhlthau. 2004. Seeking Meaning: a process approach to library and information services". Ablex Publishing.Google ScholarGoogle Scholar
  18. C. Lallemand, G. Groniera, and V. Koenig. 2015. User experience: A concept without consensus? Exploring practitioners' perspectives through an international survey. Computers in Human Behavior 43 (2015), 35--48. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. L. Luce. 2019. Artificial Intelligence for Fashion: How AI is Revolutionizing the Fashion Industry. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. MPASS. 2016. ATHMessenger, Athens International Airport chatbot. http://www.mpass.gr/blog-entry/athmessenger-chatbot-through-twitter-athens-international-airport.Google ScholarGoogle Scholar
  21. OpenJav. 2019. Official Website. http://www.openjawtech.com/.Google ScholarGoogle Scholar
  22. P. Papadopoulou. 2007. Applying virtual reality for trust-building e-commerce environments. Virtual Reality 11, 2 (2007), 107--127.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. K. Brandl R. Standefer, K. Iqbal. 2019. Key concepts in Direct Line API 3.0. https://docs.microsoft.com/en-us/azure/bot-service/rest-api/bot-framework-rest-direct-line-3-0-concepts?view=azure- bot-service-4.0.Google ScholarGoogle Scholar
  24. A. Rahman, A. Al Mamun, and A. Islam. 2017. Programming challenges of chatbot: Current and future prospective. In IEEE Region 10 Humanitarian Technology Conference. 75--78.Google ScholarGoogle Scholar
  25. R.W. Schmidt. 2018. Learning System Customer Service Chatbot. Georgia Tech Library (2018).Google ScholarGoogle Scholar
  26. J.H. Song and M.G. Zinkhan. 2008. Determinants of Perceived Web Site Interactivity. Journal of Marketing 72 (2008), 99--113.Google ScholarGoogle ScholarCross RefCross Ref
  27. S.E.A. S.p.A. 2018. Milano Malpensa WebSite - News chat-Bot. http://www.milanomalpensa-airport.com/en/airport/news?newsId=1856.Google ScholarGoogle Scholar
  28. O. Turel and C. Connelly. 2013. Too busy to help: Antecedents and outcomes of interactional justice in web-based service encounters. Int. Jour. of Information Management 33, 4 (2013), 674--683.Google ScholarGoogle ScholarCross RefCross Ref
  29. J.C. Wong. 2016. What is a chat bot, and should I be using one? | The Guardian. https://www.theguardian.com/technology/2016/apr/06/what-is-chat-bot-kik-bot-shop-messaging-platform.Google ScholarGoogle Scholar

Index Terms

  1. Design and implementation of an airport chatbot

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        GoodTechs '19: Proceedings of the 5th EAI International Conference on Smart Objects and Technologies for Social Good
        September 2019
        272 pages
        ISBN:9781450362610
        DOI:10.1145/3342428

        Copyright © 2019 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 25 September 2019

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed limited

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader