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Pix2Trips - a System Supporting Small Groups of Urban Tourists

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Konferencja
Federated Conference on Computer Science and Information Systems (16 ; 02-05.09.2021 ; online)
Języki publikacji
EN
Abstrakty
EN
Group recommendation systems are the subject of many publications, but still is a gap between research results and group decision support systems' needs. Tourists often do not know which attractions they would like to visit, our Pix2Trips system asks the group's members to indicate images that, in their opinion, they would like. Pix2Trips models the group's preferences and adjusts it to the proposed places' models. Some tourist places in Wroclaw city, Poland, were used in experiments. The paper presents the system's components and discusses the results of the experiments. Conclusions indicate the good overall evaluation of the Pix2Trips system.
Rocznik
Tom
Strony
141--145
Opis fizyczny
Bibliogr. 21 poz., wykr., tab., rys., wz.
Twórcy
  • Wroclaw University of Science and Technology, wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland
  • Chaos Group Bulgaria
Bibliografia
  • 1. Johansen, R.: Teams for Tomorrow (groupware). In: Proc. of the Twenty-Fourth Annual Hawaii International Conf. on System Sciences. 3, Decision support and knowledge-based systems and collaboration technology, 521–534, IEEE Comput. Soc.Press (1991).
  • 2. Werthner, H., et al.: Future Research Issues in IT and Tourism. Information Technology & Tourism, 15(1), 1–15 (2015).
  • 3. Felfernig, A. et al: Algorithms for Group Recommendation. In Group Recommender Systems, Springer Intern. Publishing, (2018) 27–58.
  • 4. Masthoff, J.: Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewer. In Personalized digital television. Springer, 93–141 (2004).
  • 5. Nguyen, T. N.: Conversational Group Recommender Systems. In Proc. of the 25th Conf. on User Modeling, Adaptation and Personalization, 331–334 (2017).
  • 6. Neidhardt, J. et al: A Picture-Based Approach to Recommender Systems. Information Technology & Tourism 15(1), 49–69 (2015). DOI:10.1007s40558-014-0017-5.
  • 7. Goldberg, L. R.: An Alternative "Description of Personality": The Big-Five Factor Structure. Journal of Personality and Social Psychology 59(6), 1216–1229 (1990).
  • 8. Gibson, H., Yiannakis, A.: Tourist Roles - Needs and the Lifecourse. Annals of Tourism Research 29(2), 358–383 (2002).
  • 9. Glatzer, L., Neidhardt, J., Werthner, H.: Automated Assignment of Hotel Descriptions to Travel Behavioural Patterns. In Information and Communication Technologies in Tourism, Stangl, B. and Pesonen, J., Eds., Springer, 409–421 (2018).
  • 10. Berger, H. et al: Quo Vadis Homo Turisticus? Towards a Picture-Based Tourist Profiler. In Information and Communication Technologies in Tourism, Sigala, M. et al. Eds., Springer, Vienna 87–96 (2007).
  • 11. Linaza, M. T. et al: Image-Based Travel Recommender System for Small Tourist Destinations. In Information and Communication Technologies in Tourism , Law, R. et al Eds., Springer Vienna, 1–12 (2011).
  • 12. Masthoff, J.: Group Recommender Systems: Combining Individual Models. In Recommender Systems Handbook, Ricci, F. et al Eds., Springer, 677–702 (2011).
  • 13. Ardissono, L. et al: INTRIGUE: Personalized Recommendation of Tourist Attractions for Desktop and Hand Held Devices. Applied Artificial Intelligence 17(8-9), 687–714 (2003). DOI:10.1080713827254
  • 14. Nguyen, T. N. and Ricci, F.: A Chat-Based Group Recommender System for Tourism. Information Technology & Tourism 18(1-4), 5–28 (2018).
  • 15. Álvarez Márquez, J. O., Ziegler, J.: Hootle+: A Group Recommender System Supporting Preference Negotiation. In Collaboration and Technology, Yuizono, T. et al Eds., 9848, Springer, 151–166 (2016). DOI:10.1007978-3-319-44799-5_12.
  • 16. Binucci, C. et al: Designing the Content Analyzer of a Travel Recommender System. Expert Systems with Applications 87, 199–208 (2017).
  • 17. Brooke, J.: SUS – A Quick and Dirty Usability Scale. In Usability evaluation in industry. CRC Press, 189–194 (1996).
  • 18. Bangor, A. et al: An Empirical Evaluation of the System Usability Scale. Intern. Journal of Human-Computer Interaction. 24(6), 574–594 (2008).
  • 19. Pu, P. and Chen, L.: A User-Centric Evaluation Framework of Recommender Systems. In Proceedings of the ACM RecSys Workshop on User-Centric Evaluation of Recommender Systems and Their Interfaces 612, 14–21, (2010).
  • 20. Hogg, M. A. and Hains, S. C.: Friendship and Group Identification: A New Look at the Role of Cohesiveness in Groupthink. European Journal of Social Psychology 28(3), 323–341 (1998).
  • 21. Dawes, J.: Do Data Characteristics Change According to the Number of Scale Points Used? An Experiment Using 5-Point, 7-Point and 10-Point Scales. International Journal of Market Research 50(1), 61–104 (2008).
Uwagi
1. Track 1: Artificial Intelligence in Applications
2. Session: 15th International Symposium Advances in Artificial Intelligence and Applications
3. Short Paper
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7225dd63-c826-4a4c-bda8-3e425069fac3
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