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E-tourism recommender systems: a survey and development perspectives

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper describes main modern tendencies of the design and development of intelligent information technologies, implementing process of generating recommendations in tourism recommender systems. The basic trends of the e-tourism information technology tools are analyzed to show importance of creation for multitask, multykontent mobile e-tourism recommender systems with decision support functions in terms of the tourism group, which is regarded as a single collective user.
Twórcy
autor
  • PHEE Bukovinian University
autor
  • Lviv Polytechnic National University
autor
  • Lviv Polytechnic National University
Bibliografia
  • 1. Artemenko O. 2015 Dynamic characteristics of perspective touristic information technologies / Olga Artemenko, Natalya Kunanec, Volodymyr Pasichnyk, Valeriya Savchuk // Econtechmod an international quarterly journal, No. 4, Vol. 4, рр. 107–118.
  • 2. Bin R. 2014 Research on Tourism Service Intelligent Recommendation System Based on Apriori-MD Algorithm / Rao Bin // Applied Mechanics and Materials, Vols. 651–653, рр. 1642–1646. © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.651-653.1642
  • 3. Borrаs J. 2014 Intelligent tourism recommender systems: Asurvey / J. Borrаs,A. Moreno, A. Valls // Expert Systems with Applications, Vol. 41, рр. 7370–7389.
  • 4. Cathy H. C. Hsu 2004 Image assessment for a destination with limited comparative advantages / Cathy H.C. Hsu, Kara Wolfe, Soo K. Kang // Tourism Management, Vol. 25, рр. 121–126.
  • 5. Cheng Eddie W. L. 2007 A GIS approach to shopping mall location selection / Eddie W.L. Cheng, Heng Li, Ling Yu // Building and Environment, Vol. 42, рр. 884–892.
  • 6. Eriksson N. 2010 The intended use of mobile tourism services / N. Eriksson, P. Strandvik // IADISInternational ConferenceWWW/Internet, рр. 11–18.
  • 7. Fukuda T. 2011 Development of tourism management supporting system which can collect tourist’s aspects / T. Fukuda, Y. Yoshikawa, N. Yabuki // Journal of Environment Engineering. – Apr., 2011, Vol. 76, No. 662, рр. 449–458.
  • 8. Glybovets A.М. 2009, Methods of construction of the effective distributed systems of intelligent type with application the agent approach. Thesis for a candidate degree on physics and mathematics (Ph.D.) by speciality 01.05.03 – mathematical and software support of computing systems. – Taras Shevchenko Kiev National University, Kyiv.
  • 9. Jannach D. 2010, Recommender Systems: An Introduction / D. Jannach, M. Zanker, A. Felfernig, G. Friedrich – Cambridge University Press, New York, 352 p.
  • 10. Kask S. 2011, Modeling tourist and community decision making. The SAVE Market / S. Kask, C. Kline, K. Lamoureux, Annals of Tourism Research, Vol. 38, No. 4, рр. 1387–1409.
  • 11. Кunanets N. 2016 The technology of hierarchical agglomerative cluster analysis in library research // ECONTECHMOD. AN INTERNATIONAL QUARTERLY JOURNAL , Vol. 5, No. 1, рр. 35–41
  • 12. Moore K. 2012 Dynamic in-destination decisionmaking: An adjustment model / K.Moore, C. Smallman, J. Wilson, D. Simmons // Tourism Management, Vol. 33, рр. 635–645.
  • 13. Ngai E.W.T. 2003, Design and development ofa fuzzy expert system for hotel selection / E.W.T. Ngai, F.K.T. Wat // OmegaЮ No. 31, рр. 275–286.
  • 14. Pawara P. 2014 Valuable Tourism Information viaMobile Application / Pornntiwa Pawara, Manasawee Kaenampornpan, Khanabhorn Kawattikul // Advanced Materials Research, 2014, Vols. 1044–1045, рр. 1428–1432. Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMR.1044–1045.1428.
  • 15. Ricci F. 2011, Recommender Systems Handbook / F. Ricci, L. Rokach, B. Shapira,P. B. Kantor – Springer, 875 p.
  • 16. Ricci F. 2015 Recommender Systems Handbook: Second Edition / Francesco Ricci, Lior Rokach, Bracha Shapira – Springer Science+Business Media New York, 1003 p. – ISBN 978-1-4899-7636-9.
  • 17. Stevens D. 2007 iCity: A GISeCA modelling tool for urban planning and decision making / D. Stevens, S.Dragicevic, K. Rothley// Environmental Modelling & Software, Vol. 22, рр. 761–773.
  • 18. Wang Chao-Hung 2004, Predicting tourism demand using fuzzy time series and hybrid grey theory / Chao-Hung Wang // Tourism Management, No. 25, рр. 367–374.
  • 19. Wang J. 2004 Study on modeling for choice of the best tourism based on analytic hierarchy process / Jirong Wang, Mengtian Cui, Hao Yang // Applied Mechanics and Materials, Vols. 644–650 (2014), рр. 5828–5831.
  • 20. Wang N. 2014 Research on Construction of Smart Tourism Perception System and Management Platform / Ning Wang // Applied Mechanics and Materials, Vols. 687–691, рр. 1745–1748 © (2014) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/AMM.687-691.1745.
  • 21. Yang Huanhe 2014 Based on geograpfic information system of tourism resources and circuit management system design and implementation // Applied Mechanics and Materials, Vols. 599–601, рр. 2092–2095.
  • 22. Yoon S. 2015, Design and Implementation of Mobile Game System for Vitalization of Culture Tourism / Sungwook Yoon, Hyenki Kim // International Journal of Multimedia and Ubiquitous Engineering, No. 4, Vol. 10, рр. 11–18. http://dx.doi.org/10.14257/ijmue.2015.10.4.02.
  • 23. Yue Cui 2015 Edward Mahoney Employing Internet GIS Surveys to Characterize Recreational Boating Travel Patterns // Transactions in GIS, 2015, 19(1), рр. 42–62.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-1721800e-1857-4628-8856-953fb2c45c83
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