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Social Networks Based Framework for Recommending Touristic Locations

  • Conference paper
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Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10448))

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Abstract

Tourists need tools that can help them to select locations in which they can spend their holidays. We have multiple social networks in which we find information about hotels and about users’ experiences. The problem is how tourists can use this information to build their proper opinion about a particular location to decide if they should go to that place or not. We try in this paper to present a design of a solution that can be used to achieve this task. In this paper, we propose a framework for a recommender system that bases on opinions of persons on the one hand and on of users’ preferences on the other hand to generate recommendations. Indeed, opinions of tourists are extracted from different sources and analyzed to finally extract how the hotels are perceived by their customers in terms of features and activities. The final step consists in matching between these opinions and the users’ preferences to generate the recommendations. A prototype was developed in order to show how this framework is really working.

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References

  1. TripAdvisor. https://www.tripadvisor.com/ (2016). Accessed Sept 2016

  2. Booking. http://www.booking.com/ (2016). Accessed Sept 2016

  3. TripBarometer: Yearly TripAdvisor Report. Accessed Sept 2016

    Google Scholar 

  4. Borràsa, J., Morenob, A., Vallsb, A.: Intelligent tourism recommender systems: a survey. Expert Syst. Appl. 41, 7370–7389 (2014)

    Article  Google Scholar 

  5. Cenamor, I., de la Rosa, T., Núñez, S., Borrajo, D.: Planning for tourism routes using social networks. Expert Syst. Appl. 69, 1–9 (2017)

    Article  Google Scholar 

  6. Castilloa, L., Armengolb, E., Onaindíac, E., Sebastiác, L., González-Boticariod, J., Rodríguezd, A., Fernándeze, S., Ariase, J.D., Borrajo, D.: SAMAP: an user-oriented adaptive system for planning tourist visits. Expert Syst. Appl. 34, 1318–1332 (2008)

    Article  Google Scholar 

  7. Loh, S., Lorenzi, F., Saldana, R., Licthnow, D.: A tourism recommender system based on collaboration and text analysis. Inf. Technol. Tour. 6, 157–165 (2003)

    Article  Google Scholar 

  8. Schiaffino, S., Amandi, A.: Building an expert travel agent as a software agent. Expert Syst. Appl. 36, 1291–1299 (2009)

    Article  Google Scholar 

  9. Khoshnood, F., Mahdavi, M., Sarkaleh, M.K.: Designing a recommender system based on social networks and location based services. Int. J. Manag. Inf. Technol. 4, 41–47 (2012)

    Google Scholar 

  10. Husain, W., Dih, L.Y.: A framework of a personalized location-based traveler recommendation system in mobile application. Int. J. Multimed. Ubiquitous Eng. 7, 11–18 (2012)

    Google Scholar 

  11. Ravi, L., Vairavasundaram, S.: A collaborative location based travel recommendation system through enhanced rating prediction for the group of users. Comput. Intell. Neurosci. 2016, 7 (2016). Article ID 1291358

    Article  Google Scholar 

  12. Fernandez, Y.B., Nores, M.L., Arias, J.J.P., Duque, J.G., Vicente, M.I.M.: TripFromTV+: exploiting social networks to arrange cut-price touristic packages. In: Proceedings of IEEE International Conference on Costumer Electronics, pp. 223–224 (2011)

    Google Scholar 

  13. Garcia, I., Sebastia, L., Onaindia, E.: On the design of individual and group recommender systems for tourism. Expert Syst. Appl. 38, 7683–7692 (2011)

    Article  Google Scholar 

  14. García-Crespo, Á., López-Cuadrado, J.L., Colomo-Palacios, R., González-Carrasco, I., Ruiz-Mezcua, B.: Sem-fit: a semantic based expert system to provide recommendations in the tourism domain. Expert Syst. Appl. 38, 13310–13319 (2011)

    Article  Google Scholar 

  15. Batet, M., Moreno, A., Sánchez, D., Isern, D., Valls, A.: Turist@: agent-based personalized recommendation of tourist activities. Expert Syst. Appl. 39, 7319–7329 (2012)

    Article  Google Scholar 

  16. Frikha, M., Mhiri, M., Gargorui, F.: A semantic social recommender system using ontologies based approach for tunisian tourism. Adv. Distrib. Comput. Artif. Intell. J. 4, 90–106 (2015)

    Google Scholar 

  17. Chang, W., Ma, L.: Personalized E-tourism attraction recommendation based on context. In: Proceedings of 10th International Conference on Service Systems and Service Management, Hong Kong, pp. 674–679 (2013)

    Google Scholar 

  18. Pai, P.-F., Hung, K.-C., Lin, K.-P.: Tourism demand forecasting using novel hybrid system. Expert Syst. Appl. 41(8), 3691–3702 (2014)

    Article  Google Scholar 

  19. Gate—A General Architecture for Text Engineering Documentation. http://gate.ac.uk. Accessed Sept 2016

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Author information

Authors and Affiliations

  1. Research Group on Intelligent Machines, ENIS, University of Sfax, BP 1173, 3038, Sfax, Tunisia

    Mehdi Ellouze

  2. Luxembourg Institute of Science and Technology, 5 Avenue des Hauts-Fourneaux, 4362, Esch-sur-Alzette, Luxembourg

    Slim Turki, Younes Djaghloul & Muriel Foulonneau

Authors
  1. Mehdi Ellouze
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  2. Slim Turki
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  3. Younes Djaghloul
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  4. Muriel Foulonneau
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Corresponding author

Correspondence to Mehdi Ellouze .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management , Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of Münster, Münster, Germany

    Gottfried Vossen

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© 2017 Springer International Publishing AG

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Ellouze, M., Turki, S., Djaghloul, Y., Foulonneau, M. (2017). Social Networks Based Framework for Recommending Touristic Locations. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_17

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  • DOI: https://doi.org/10.1007/978-3-319-67074-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67073-7

  • Online ISBN: 978-3-319-67074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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