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Context-aware tourism technologies

Published online by Cambridge University Press:  04 September 2018

Fátima Leal ,
Benedita Malheiro  and
Juan C. Burguillo Open the ORCID record for Juan C. Burguillo [Opens in a new window]
Fátima Leal
Affiliation:
Department of Telematic Engineering, School of Telecommunications Engineering (EET), University of Vigo, Campus Universitario Lagoas, Marcosende, 36200 Vigo, Spain e-mail: fatimaleal2@gmail.com, J.C.Burguillo@uvigo.es INESC TEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal e-mail: mbm@isep.ipp.pt
Benedita Malheiro
Affiliation:
Department of Electrical Engineering, School of Engineering (ISEP), Porto Polytechnic, Rua Dr. António Bernardino de Almeida, 431, 4249-015 Porto, Portugal INESC TEC, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal e-mail: mbm@isep.ipp.pt
Juan C. Burguillo
Affiliation:
Department of Telematic Engineering, School of Telecommunications Engineering (EET), University of Vigo, Campus Universitario Lagoas, Marcosende, 36200 Vigo, Spain e-mail: fatimaleal2@gmail.com, J.C.Burguillo@uvigo.es
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Abstract

Nowadays travellers can benefit from the computing capabilities, collection of on board sensors and ubiquitous Internet access provided by mobile devices. These are the three pillars of any tourist support system since they provide the power, means and data to establish the local user context, to access remote services and to provide value-added user-centred context-aware applications. However, making sense of the user context data is not straightforward, as it requires dedicated knowledge acquisition and knowledge representation solutions. Besides, the range and diversity of available data sources is huge, requiring appropriate knowledge processing techniques to provide addequated tourism services. This article presents an updated review, and a comparison of recent context-aware tourism applications (CATA), including supporting technologies; and considering four possible dimensions: knowledge acquisition, knowledge representation, knowledge processing and knowledge-based services. We propose and apply a CATA analysis framework, contemplating these four dimensions to the applications found in the literature. This survey constitutes, not only, a state of the art review on tourism mobile applications, but, also, anticipates the latest development trends in tourism-related applications.

Type
Survey Article
Information
The Knowledge Engineering Review , Volume 33 , 2018 , e13
Copyright
© Cambridge University Press, 2018 

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References

Abowd, G. D., Dey, A. K., Brown, P. J., Davies, N., Smith, M. & Steggles, P. 1999. Towards a better understanding of context and context-awareness. In Handheld and Ubiquitous Computing, Gellersen, H.-W., (ed.). Springer Berlin, 304–307.Google Scholar
Adomavicius, G. & Tuzhilin, A. 2005. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749.Google Scholar
Adomavicius, G. & Tuzhilin, A. 2015. Context-Aware Recommender Systems. Springer, 191–226.Google Scholar
Albu, C.-E. 2013. Stereotypical factors in tourism. Cross-Cultural Management Journal (3), 5–13.Google Scholar
Amatriain, X. 2013. Mining large streams of user data for personalized recommendations’. SIGKDD Explorotions Newsletter 14(2), 37–48.Google Scholar
Anacleto, R., Figueiredo, L., Luz, N., Almeida, A. & Novais, P. 2011. Recommendation and planning through mobile devices in tourism context. In Ambient Intelligence – Software and Applications, Novais, P., Preuveneers, D. & Corchado, J. M. (eds). Springer Berlin, 133–140.Google Scholar
Ashley-Dejo, E., Ngwira, S. M. & Zuva, T. 2016. A context-aware proactive recommender system for tourist. In 2016 International Conference on Advances in Computing and Communication Engineering (ICACCE), 271–275.Google Scholar
Bahramian, Z., Ali Abbaspour, R. & Claramunt, C. 2017. A cold start context-aware recommender system for tour planning using artificial neural network and case based reasoning. In Mobile Information Systems 2017.Google Scholar
Baltrunas, L., Ludwig, B., Peer, S. & Ricci, F. 2011. Context-aware places of interest recommendations for mobile users. In International Conference of Design, User Experience, and Usability, 531–540. Springer.Google Scholar
Barragáns-Martínez, A. B. & Costa-Montenegro, E. 2015. Adding personalization and social features to a context-aware application for mobile tourism. In Hospitality, Travel, and Tourism: Concepts, Methodologies, Tools and Applications. IGI Global, 467–480.Google Scholar
Batet, M., Moreno, A., Sánchez, D., Isern, D. & Valls, A. 2012. Turist@: agent-based personalised recommendation of tourist activities. Expert Systems with Applications 39(8), 7319–7329.Google Scholar
Borras, J., Moreno, A. & Valls, A. 2014. Intelligent tourism recommender systems: a survey. Expert Systems with Applications 41(16), 7370–7389.Google Scholar
Braunhofer, M., Elahi, M. & Ricci, F. 2014. Techniques for cold-starting context-aware mobile recommender systems for tourism. Intelligenza Artificiale 8(2), 129–143.Google Scholar
Brewster, C. & O’Hara, K. 2004. Knowledge representation with ontologies: the present and future. IEEE Intelligent Systems 19(1), 72–81.Google Scholar
Bruyneel, K. & Malheiro, B. 2014. Erasmusapp: a location-based collaborative system for erasmus students. In ECUMICT 2014, 35–47. Springer.Google Scholar
Burke, R. 2002. Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction 12(4), 331–370.Google Scholar
Cárcel, G. H., Campo, A., Gil, M., Garcia, A., Martin, D., Zugasti, I., Bilbao, S., Perez, A., Koshutanski, H., Maña, A. & De Albeniz, I. P., 2012. ConTur: an intelligent content management system for the tourism sector. In Information and Communication Technologies in Tourism, Fuchs, M., Ricci, F. & Cantoni, L. (eds). Springer.Google Scholar
Castillo, L., Armengol, E., Onaindía, E., Sebastiá, L., González-Boticario, J., Rodríguez, A., Fernández, S., Arias, J. D. & Borrajo, D. 2008. Samap: An user-oriented adaptive system for planning tourist visits. Expert Systems with Applications 34(2), 1318–1332.Google Scholar
Ceccaroni, L., Codina, V., Palau, M. & Pous, M. 2009. Patac: Urban, ubiquitous, personalized services for citizens and tourists. In Third International Conference on Digital Society, 2009. ICDS’09, 7–12. IEEE.Google Scholar
Chen, G. & Kotz, D. 2000. A Survey of Context-Aware Mobile Computing Research. Technical Report TR2000-381, Department of Computer Science, Dartmouth College.Google Scholar
Colomo-Palacios, R., García-Peñalvo, F. J., Stantchev, V. & Misra, S. 2017. Towards a social and context-aware mobile recommendation system for tourism, Pervasive and Mobile Computing 38, 505–515. In Special Issue IEEE International Conference on Pervasive Computing and Communications (PerCom) 2016, http://www.sciencedirect.com/science/article/pii/S1574119216000407.Google Scholar
de la Flor, J., Borràs, J., Isern, D., Valls, A., Moreno, A., Russo, A., Pérez, Y. & Anton-Clavé, S. 2012. Semantic enrichment for geospatial information in a tourism recommender system. In Discovery of Geospatial Resources: Methodologies, Technologies, and Emergent Applications, 133–155. IGI Global.Google Scholar
Dell’Erba, M., Fodor, O., Ricci, F. & Werthner, H. 2003. Harmonise: a solution for data interoperability. In Towards the Knowledge Society, 433–445. Springer.Google Scholar
Dey, A. K. 2001. Understanding and using context. Personal and Ubiquitous Computing 5(1), 4–7.Google Scholar
Gama, J. 2010. Knowledge Discovery from Data Streams. CRC Press.Google Scholar
Garcia, A., Torre, I. & Linaza, M. T. 2013. Mobile social travel recommender system. In Information and Communication Technologies in Tourism 2014, 3–16. Springer.Google Scholar
García-Crespo, A., Chamizo, J., Rivera, I., Mencke, M., Colomo-Palacios, R. & Gómez-Berbís, J. M. 2009. Speta: social pervasive e-tourism advisor. Telematics and Informatics 26(3), 306–315.Google Scholar
Gavalas, D., Konstantopoulos, C., Mastakas, K. & Pantziou, G. 2014. Mobile recommender systems in tourism. Journal of Network and Computer Applications 39, 319–333.Google Scholar
Grimm, S. 2010. Knowledge representation and ontologies. In Scientific Data Mining and Knowledge Discovery.Google Scholar
Gula, I. 2013. Crowdsourcing in the tourism industry—using the example of ideas competitions in tourism destinations. In ISCONTOUR 2013: Proceedings of the International Student Conference in Tourism Research, 147. BoD-Books on Demand.Google Scholar
Han, J. & Ding, B. 2009. Stream Mining. Springer, 2831–2834.Google Scholar
Herath, H. & Ratnayake, H. 2013. Multi agent system for trip planning. In 2013 8th International Conference on Computer Science & Education (ICCSE), 298–303. IEEE.Google Scholar
Hildebrandt, M. 2006. Profiling: from data to knowledge. Datenschutz und Datensicherheit-DuD 30(9), 548–552.Google Scholar
Hildebrandt, M. 2008. Defining profiling: a new type of knowledge? In Profiling the European citizen, 17–45. Springer.Google Scholar
Howe, J. 2006. The rise of crowdsourcing. Wired Magazine 14(6), 1–4.Google Scholar
Hung, J. C., Hsu, V. & Wang, Y.-B. 2011. A smart-travel system based on social network service for cloud environment. In 2011 Third International Conference on Intelligent Networking and Collaborative Systems (INCoS), 514–519. IEEE.Google Scholar
Jøsang, A., Ismail, R. & Boyd, C. 2007. A survey of trust and reputation systems for online service provision. Decision Support Systems 43(2), 618–644.Google Scholar
Kashevnik, A. M., Ponomarev, A. V. & Smirnov, A. V. 2017. A multimodel context-aware tourism recommendation service: approach and architecture. Journal of Computer and Systems Sciences International 56(2), 245–258.Google Scholar
Kingston, J. K. 1998. Designing knowledge based systems: the commonkads design model. Knowledge-Based Systems 11(5), 311–319.Google Scholar
Kiryakov, A., Popov, B., Terziev, I., Manov, D. & Ognyanoff, D. 2004. Semantic annotation, indexing, and retrieval. Web Semantics: Science, Services and Agents on the World Wide Web 2(1), 49–79.Google Scholar
Legrand, B. 2004. Semantic web methodologies and tools for intra-European sustainable tourism, White paper, Mondeca.Google Scholar
Li, X., Eckert, M., Martinez, J.-F. & Rubio, G. 2015. Context aware middleware architectures: survey and challenges. Sensors 15(8), 20570–20607.Google Scholar
Luz, N., Anacleto, R. & Almeida, A. 2010. Tourism mobile and recommendation systems-a state of the art. In Proceedings of the 2010 International Conference on E-Learning, E-Business, Enterprise Information Systems, & E-Government (EEE2010), 277–283. CSREA EEE.Google Scholar
Martin, D., Alzua, A. & Lamsfus, C. 2011. A contextual geofencing mobile tourism service. In ENTER, 191–202.Google Scholar
Meehan, K., Lunney, T., Curran, K. & McCaughey, A. 2013. Context-aware intelligent recommendation system for tourism. In 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), 328–331. IEEE.Google Scholar
Middleton, S. E., Shadbolt, N. R. & De Roure, D. C. 2004. Ontological user profiling in recommender systems. ACM Transactions on Information Systems (TOIS) 22(1), 54–88.Google Scholar
Missikoff, M. & Taglino, F. 2004. An ontology-based platform for semantic interoperability. In Handbook on Ontologies. International Handbooks on Information Systems, Staab, S. & Studer, R. (eds). Springer, 617–633.Google Scholar
Musumba, G. W. & Nyongesa, H. O. 2013. Context awareness in mobile computing: a review. International Journal of Machine Learning and Applications 2(1), 5.Google Scholar
Najafian, S., Wörndl, W. & Braunhofer, M. 2016. Context-aware user interaction for mobile recommender systems. In Late-breaking Results, Posters, Demos, Doctoral Consortium and Workshops Proceedings of the 24th ACM Conference on User Modeling, Adaptation and Personalisation (UMAP 2016), Halifax, July 13–16.Google Scholar
Noguera, J. M., Barranco, M. J., Segura, R. J. & MartíNez, L. 2012. A mobile 3d-gis hybrid recommender system for tourism’. Information Sciences 215, 37–52.Google Scholar
Ou, S., Pekar, V., Orasan, C., Spurk, C. & Negri, M. 2008. Development and alignment of a domain-specific ontology for question answering. In LREC.Google Scholar
Panahi, M. S., Woods, P. & Thwaites, H. 2013. Designing and developing a location-based mobile tourism application by using cloud-based platform. In 2013 International Conference on Technology, Informatics, Management, Engineering, and Environment (TIME-E), 151–156. IEEE.Google Scholar
Poveda Villalon, M., Suàrez-Figueroa, M. C., García-Castro, R. & Gómez-Pérez, A. 2010. A context ontology for mobile environments. In Proceedings of the Second Workshop on Context, Information and Ontologies Google Scholar
Prantner, K. 2004. Ontour: The ontology, Deri Insbruck.Google Scholar
Prantner, K., Ding, Y., Luger, M., Yan, Z. & Herzog, C. 2007. Tourism ontology and semantic management system: state-of-the-arts analysis. In IADIS international conference WWW/Internet, 111–115.Google Scholar
Qureshi, S. S., Ahmad, T. & Rafique, K. 2011. Mobile cloud computing as future for omobile applications-implementation methods and challenging issues. In 2011 IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 467–471. IEEE.Google Scholar
Raento, M., Oulasvirta, A., Petit, R. & Toivonen, H. 2005. Contextphone: a prototyping platform for context-aware mobile applications. IEEE Pervasive Computing 4(2), 51–59.Google Scholar
Ren, Y., Li, G. & Zhou, W. 2015. A survey of recommendation techniques based on offline data processing. Concurrency and Computation: Practice and Experience 27(15), 3915–3942.Google Scholar
Rodríguez, J., Bravo, M. & Guzmán, R. 2012. Multi-dimensional ontology model to support context-aware systems. In International Conference on Internet and Web Applications and Services, 80–89.Google Scholar
Santiago, F. M., López, F. A., Montejo-Ráez, A. & López, A. U. 2012. Geoasis: a knowledge-based geo-referenced tourist assistant. Expert Systems with Applications 39(14), 11737–11745.Google Scholar
Sayed-Mouchaweh, M. 2016. Learning from Data Streams in Dynamic Environments. Springer.Google Scholar
Schiaffino, S. & Amandi, A. 2009. Intelligent user profiling. In Artificial Intelligence An International Perspective, M. Bramer (ed.), Lecture Notes in Computer Science 5640, 193–216. Springer Berlin.Google Scholar
Sigala, M. 2015. Gamification for crowdsourcing marketing practices: applications and benefits in tourism. In Advances in Crowdsourcing, 129–145. Springer.Google Scholar
Sigala, M., Christou, E. & Gretzel, U. 2012. Social Media in Travel, Tourism and Hospitality: Theory, Practice and Cases. Ashgate Publishing Ltd.Google Scholar
Silva, C. A., Toasa, R., Guevara, J., Martinez, H. D. & Vargas, J. 2018. Mobile application to encourage local tourism with context-aware computing. In Proceedings of the International Conference on Information Technology & Systems (ICITS 2018), Rocha, Á. & Guarda, T. (eds), 796–803. Springer International Publishing.Google Scholar
Siricharoen, W. V. 2007. Using ontologies for e-tourism. In The 4th WSEAS/IASME International Conference on Engineering Education (EE 2007) Proceeding.Google Scholar
Smirnov, A., Kashevnik, A., Balandin, S. I. & Laizane, S. 2013. Intelligent mobile tourist guide. In Internet of Things, Smart Spaces, and Next Generation Networking, Balandin, S., Andreev, S. & Koucheryavy, Y. (eds). Springer Berlin, 94–106.Google Scholar
Stephan, G. S., Pascal, H. S. & Andreas, A. S. 2007. Knowledge Representation and Ontologies. Springer.Google Scholar
Su, X. & Khoshgoftaar, T. M. 2009. A survey of collaborative filtering techniques. Advances in Artificial Intelligence 2009, 4.Google Scholar
Umanets, A., Ferreira, A. & Leite, N. 2014. Guideme-a tourist guide with a recommender system and social interaction. Procedia Technology 17, 407–414.Google Scholar
Viktoratos, I., Tsadiras, A. & Bassiliades, N. 2014. A rule-based service for context-aware point of interest exploration. In Proceedings of the CEUR Workshop.Google Scholar
Viktoratos, I., Tsadiras, A. & Bassiliades, N. 2015. A context-aware web-mapping system for group-targeted offers using semantic technologies. Expert Systems with Applications 42(9), 4443–4459.Google Scholar
Wang, D., Park, S. & Fesenmaier, D. R. 2012. The role of smartphones in mediating the touristic experience. Journal of Travel Research 51(4), 371–387.Google Scholar
Yang, W.-S. & Hwang, S.-Y. 2013. itravel: a recommender system in mobile peer-to-peer environment. Journal of Systems and Software 86(1), 12–20.Google Scholar