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Editor-in-Chief
Nikiforov
Vladimir O.
D.Sc., Prof.
Partners
doi: 10.17586/2226-1494-2019-19-3-499-507
INTELLIGENT TOURIST ASSISTANCE SYSTEM: SERVICE-ORIENTED ARCHITECTURE AND IMPLEMENTATION
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Abstract
Mikhailov S.A. Intelligent tourist assistance system: service-oriented architecture and implementation. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 3, pp. 499–507 (in Russian). doi: 10.17586/2226-1494-2019-19-3-499-507
Abstract
Subject of Research. The paper presents research of the tourism support systems performed with modern information technologies. The subject of research is the intelligent tourist assistance system. The analysis of the existing tourist support systems is carried out and their advantages and disadvantages are given. The system architecture and implementation details are developed. A generation method for tourist attraction ratings is developed and experiments are carried out. Method. The method of description and comparative analysis of relevant systems was used for tourist support systems analysis. Machine learning methods were used to create recommendations for sightseeing. The methods of graph theory were used to build routes for places of interest visiting. Main Results. The advantages and disadvantages of the existing tourist support systems have been highlighted. The service-oriented architecture of the proposed intelligent tourist assistance system has been formulated. An attraction information generation method for the specific region based on the open specialized sources has been described. Experiments have been performed aimed at the work evaluation of the tourist assistance system. Practical Relevance. Application of the research results provides for the development of an intelligent tourist assistance system that meets modern requirements and surpasses the existing analogues.
Keywords: information system, tourism, context, services, recommending system
Acknowledgements. The presented results are part of the research carried out within the project funded by grants No. 18-37-00337, 17-29-03284 of the Russian Foundation for Basic Research. The work was partially supported by the Russian State Research No. 0073-2019-0005.
References
Acknowledgements. The presented results are part of the research carried out within the project funded by grants No. 18-37-00337, 17-29-03284 of the Russian Foundation for Basic Research. The work was partially supported by the Russian State Research No. 0073-2019-0005.
References
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2. Ulrike G., Marianna S., Zheng X., Chulmo K. Smart tourism: foundations and developments. Electronic Markets, 2015, vol. 25, no. 3, pp. 179–188. doi: 10.1007/s12525-015-0196-8
3. Borras J., Moreno A., Valls A. Intelligent tourism recommender systems: a survey. Expert Systems with Applications, 2014, vol. 41, no. 16, pp. 7370–7389. doi: 10.1016/j.eswa.2014.06.007
4. Mikhailov S., Kashevnik A. An ontology for service semantic interoperability in the smartphone-based tourist trip planning system. Proc. 23rd Conference of Open Innovations Association FRUCT. Bologna, Italy, 2018, pp. 239–245. doi: 10.23919/fruct.2018.8588027
5. Smirnov A., Kashevnik A., Ponomarev A. Context-based infomobility system for cultural heritage recommendation: tourist assistant — TAIS. Personal Ubiquitous Computing, 2017, vol. 21, no. 2, pp. 297–311. doi: 10.1007/s00779-016-0990-0
6. Long L., Jin X., Stephen S.L., Huaping C. A real-time personalized route recommendation system for self-drive tourists based on vehicle to vehicle communication. Expert Systems with Applications, 2014, vol. 41, no. 7, pp. 3409–3414. doi: 10.1016/j. eswa.2013.11.035
7. Santos F., Almeida A., Martins C., Gonçalves R., Martins J. Using POI functionality and accessibility levels for delivering personalized tourism recommendations. Computers, Environment and Urban Systems, 2017. (in press) doi: 10.1016/j. compenvurbsys.2017.08.007
8. Colomo-Palacios R., Garcia-Penalvo F.J., Stantchev V., Misra S. Towards a social and context-aware mobile recommendation system for tourism. Pervasive and Mobile Computing, 2017, vol. 38, pp. 505–515. doi: 10.1016/j.pmcj.2016.03.001
9. Zheng W., Liao Z. Using a heuristic approach to design personalized tour routes for heterogeneous tourist groups. Tourism Management, 2019, vol. 72, pp. 313–325. doi: 10.1016/j.tourman.2018.12.013
10. Moreno A., Valls A., Isern D., Marin L., Borras J. SigTur/ E-destination: ontology-based personalized recommendation of tourism and leisure activities. Engineering Applications of Artificial Intelligence, 2013, vol. 26, no. 1, pp. 633–651. doi: 10.1016/j.engappai.2012.02.014
11. Cenamor I., Rosa T., Nez S. Borrajo D. Planning for tourism routes using social networks. Expert Systems with Applications, 2017, vol. 69, pp. 1–9. doi: 10.1016/j.eswa.2016.10.030
12. Xiaoting W., Christopher L., Jeffrey C., Hui L.K., Tharshan V. Improving personalized trip recommendation by avoiding crowds. Proc. 25th ACM Int. Conf. on Information and
Knowledge Management. Indianapolis,USA, 2016, pp. 25–34. doi: 10.1145/2983323.2983749
13. Papadakis H., Panagiotakis C., Fragopoulou P. SCoR: a synthetic coordinate based recommender system. Expert Systems with Applications, 2017, vol. 79, pp. 8–19. doi: 10.1016/j.eswa.2017.02.025
14. Kashevnik A., Mikhailov S., Papadakis H., Fragopoulou P. Context-driven tour planning service: an approach based on synthetic coordinates recommendation. Proc. 24th Conference of Open Innovations Association FRUCT. Moscow, Russia, 2019.
15. Korzun D., Kashevnik A., Balandin S. Novel Design and the Applications of Smart-M3 Platform in the Internet of Things: Emerging Research and Opportunities. IGI Global, 2017, 150 p. doi: 10.4018/978-1-5225-2653-7
16. Smirnov A., Kashevnik A., Ponomarev A., Teslya N., Schekotov M., Balandin S. Smart space-based tourist recommendation system. Lecture Notes in Computer Science, 2014, vol. 8638, pp. 40–51. doi: 10.1007/978-3-319-10353-2_4
17. Mikhailov S., Kashevnik A. Smartphone-based tourist trip planning system: a context-based approach to offline attraction recommendation. MATEC Web Conf., 2018, vol. 161, art. 03026. doi: 10.1051/matecconf/201816103026