Abstract
This paper addresses the challenges to support tourists in their decision-making during the pre-trip phase and to facilitate the process of identifying those tourism objects that best fit the tourists’ preferences. The latter directly depends on the quality of the matchmaking process, i.e. finding those tourism objects that are most attractive to a particular tourist. To achieve this goal, an innovative approach is introduced that matches tourist profiles with the characteristics of tourism objects in order to obtain a ranked list of appropriate objects for a particular tourist. The matchmaking process leverages tourist factors as a shortcut to propose a first user profile and related to this, a first set of tourism objects. User feedback is then used to dynamically adapt the tourist profile and thus refine the set of recommended objects. Our approach is tested through a prototypical recommender system that suggests tourists in Vienna attractions that are tailored to their personal needs. Furthermore, a user study is conducted by asking people to interact with the system and fill in a questionnaire afterwards.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Al-Hassan, M., Lu, H., & Lu, J. (2015). A semantic enhanced hybrid recommendation approach: A case study of e-government tourism service recommendation system. Decision Support Systems, 72, 97–109.
Barta, R., Feilmayr, C., Pröll, B., Grün, C., & Werthner, H. (2009). Covering the semantic space of tourism: An approach based on modularized ontologies. In Proceedings of the 1st Workshop on Context, Information and Ontologies, CIAO ’09, ACM.
Borràs, J., Moreno, A., & Valls, A. (2014). Intelligent tourism recommender systems: A survey. In Expert Systems with Applications (Vol. 41(16)).
Brusilovsky, P., & Millán, E. (2007). User models for adaptive hypermedia and adaptive educational systems. In P. Brusilovsky, A. Kobsa & W. Nejdl (Eds.), The Adaptive Web. Lecture Notes in Computer Science (Vol. 4321), Springer.
de Gemmis, M., Lops, P., Musto, C., Narducci, F., & Semeraro, G. (2015). Semantics-Aware Content-Based Recommender Systems (pp. 119–159). Boston, MA: Springer US.
Fesenmaier, D. R., Werthner, H., & Wöber, K. W. (2006). Destination Recommendation Systems: Behavioural Foundations and Applications. Chapter Travel Destination Choice Models (pp. 3–16). CAB International.
Gibson, H., & Yiannakis, A. (2002). Tourist roles: Needs and the lifecourse. Annals of Tourism Research, 29(2), 358–383.
Gretzel, U., Mitsche, N., Hwang, Y.-H., & Fesenmaier, D. R. (2004). Tell me who you are and I will tell you where to go: Use of travel personalities in destination recommendation systems. Information Technology and Tourism, 7, 3–12.
Mínguez, I., Berrueta, D., & Polo, L. (2010). CRUZAR: An application of semantic matchmaking to e-tourism. In Cases on Semantic Interoperability for Information Systems Integration: Practices and Applications. IGI GLOBAL.
Moreno, A., Valls, A., Isern, D., Marin, L., & Borràs, J, (2013). Sigtur/e-destination: Ontology-based personalized recommendation of tourism and leisure activities. Engineering Applications of Artificial Intelligence, 26(1):633–651.
Neidhardt, J., Seyfang, L., Schuster, R., & Werthner, H. (2014). A picture-based approach to recommender systems. Information Technology and Tourism, 15(1), 49–69.
O’Connor, P. (1999). Electronic Information Distribution in Tourism and Hospitality. CABI.
Pearce, P. L., & Lee, U.-I. (2005). Developing the Travel Career Approach to Tourist Motivation. Journal of Travel Research, 43(3), 226–237.
Plog, S. (2001). Why destination areas rise and fall in popularity: an update of a cornell quarterly classic. The Cornell Hotel and Restaurant Administration Quarterly, 42(3).
Sieg, A., Mobasher, B., & Burke, R. (2007). Web search personalization with ontological user profiles. In CIKM ’07: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (pp. 525–534). ACM.
Werthner, H., Alzua, A., Cantoni, L., Dickinger, A., Gretzel, U., Jannach, D., et al. (2015). Future research issues in it and tourism. Information Technology and Tourism, 15(1), 1–15.
Xiang, Z., Gretzel, U., & Fesenmaier, D. R. (2008). Semantic representation of tourism on the internet. Journal of Travel Research.
Ziegler, C.-N., Lausen, G., & Schmidt-Thieme, L. (2004). Taxonomy-driven computation of product recommendations. In CIKM ’04: Proceedings of the 13th ACM international conference on Information and knowledge management, pp. 406–415. ACM.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Grün, C., Neidhardt, J., Werthner, H. (2017). Ontology-Based Matchmaking to Provide Personalized Recommendations for Tourists. In: Schegg, R., Stangl, B. (eds) Information and Communication Technologies in Tourism 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-51168-9_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-51168-9_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-51167-2
Online ISBN: 978-3-319-51168-9
eBook Packages: Business and ManagementBusiness and Management (R0)