Top

Quality & Quantity

Published in:

06-10-2020

Exploiting social data for tourism management: the SMARTCAL project

Authors: Annarita De Maio, Elisabetta Fersini, Enza Messina, Francesco Santoro, Antonio Violi

Published in: Quality & Quantity | Special Issue 3/2023

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

In this work we describe a new Smart Tourism System called SMARTCAL, born during the development of a R&D project for supporting the tourism digitalisation, that includes the release of a pilot in Calabria (a region in the South of Italy). The project is a new initiative to support tourism and hospitality industry with a series of statistical tools for the decision makers, to provide digital and smart services for the tourists that want to build their itineraries with flexibility and to improve the valorisation of a particular territory from the economical and tourist point of view. Indeed, the system is designed by considering Points and Events of Interest (PEOI) and their relationship with the local transport systems, with the hospitality industries and with the policy makers. Two major tools are described in the following: a proactive tourist tour planner algorithm, proposed to generate optimised itineraries based on static and dynamic profiling of the users, and a sentiment analysis module that supports decision makers with a scorecard with a set of key indicators.

previous article Emergency management and internal audit of emergency preparedness of pre-hospital emergency care

next article Economic development trends in the EU tourism industry. Towards the digitalization process and sustainability

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Alemeye, F., Getahun, F.: Cloud readiness assessment framework and recommendation system. In: AFRICON 2015. IEEE, pp. 1–5 (2015)

Alter, S.L.: Decision Support Systems: Current Practice and Continuing Challenges. Addison-Wesley, Reading (1980)

Ardissono, L., Goy, A., Petrone, G., Signan, M., Torasso, P.: Intrigue: personalized recommendation of tourism attractions for desktop and handset devices. Artif. Intell. 17(8–9), 687–714 (2003)

Ardito, L., Cerchione, R., Del Vecchio, P., Raguseo, E.: Big data in smart tourism: challenges, issues and opportunities. Curr. Issues Tour. 22, 1805–1917 (2019)CrossRef

Baggio, R., Caporarello, L.: Decision support systems in a tourism destination: literature survey and model building. In: itAIS 2005—2nd Conference of the Italian Chapter of AIS (Association for Information Systems) (2005)

Baldi, M., Fersini, E., Messina, E.: Relational Bayesian model averaging for sentiment analysis in social networks. In: Sixth International Conference on Machine Learning, Optimization, and Data Science (2020)

Batet, M., Moreno, A., Sánchez, D., Isern, D., Valls, A.: Turist@: agent-based personalised recommendation of tourist activities. Expert Syst. Appl. 39(8), 7319–7329 (2012)CrossRef

Bauer, J., Nanopoulos, A.: Recommender systems based on quantitative implicit customer feedback. Decis. Support Syst. 68, 77–88 (2014)CrossRef

Bedi, P., Agarwal, S.K., Jindal, V., Richa: MARST: multi-agent recommender system for e-tourism using reputation based collaborative filtering. In: Databases in Networked Information Systems. Springer, pp. 189–201 (2014)

Bjelica, M.: Towards TV recommender system: experiments with user modeling. IEEE Trans. Consum. Electron. 56(3), 1763–1769 (2010)CrossRef

Borràs, J., Moreno, A., Valls, A.: Intelligent tourism recommender systems: a survey. Expert Syst. Appl. 41(16), 7370–7389 (2014)CrossRef

Castillo, L.A., Armengol, E., Onaindia, E., Sebastia, L., González-Boticario, J., Rodríguez, A., Fernández, S., Arias, J.D., Borrajo, D.: SAMAP: an user-oriented adaptive system for planning tourist visits. Expert Syst. Appl. 34(2), 1318–1332 (2008)CrossRef

Ciancio, C., De Maio, A., Laganà, D., Santoro, F., Violi, A.: A genetic algorithm framework for the orienteering problem with time windows. In: New Trends in Emerging Complex Real Life Problems AIRO. Springer, pp. 179–188 (2018)

Dennison, G., Bourdage-Braun, M., Chetuparambil, S.: Social commerce defined. White Paper 23747 (2009)

Eom, S.B., Lee, S.M., Kim, E.B., Somarajan, C.: A survey of decision support system applications (1988–1994). J. Oper. Res. Soc. 49, 109–120 (1998)CrossRef

Fersini, E., Messina, E., Pozzi, F.: Sentiment analysis: Bayesian ensemble learning. Decis. Support Syst. 68, 26–38 (2014)CrossRef

Fersini, E., Pozzi, F., Messina, E.: Approval network: a novel approach for sentiment analysis in social networks. World Wide Web 20, 831–854 (2017)CrossRef

Finlay, P.N.: Introducing Decision Support Systems. Blackwell, Oxford (1994)

Gavalas, D., Konstantopoulos, C., Mastakas, K., Pantziou, G.: A survey on algorithmic approaches for solving tourist trip design problems. J. Heuristics 20, 291–328 (2014)CrossRef

Gendreau, M., Laporte, G., Semet, F.: A tabu search heuristic for the undirected selective travelling salesman problem. Eur. J. Oper. Res. 106(2), 539–545 (1998)CrossRef

Geng, X., Zhang, H., Bian, J., Chua, T.S.: Learning image and user features for recommendation in social networks. In: 2015 IEEE International Conference on Computer Vision (ICCV). IEEE, pp. 4274–4282 (2015)

Golden, B., Levy, L., Vohra, R.: The orienteering problem. Naval Res. Logist. 34, 307–318 (1987)CrossRef

Gunawan, A., Chuin Lau, H., Vansteenwegen, P.: Orienteering problem: a survey of recent variants, solution approaches and applications. Eur. J. Oper. Res. 255(2), 315–332 (2016)CrossRef

Guo, G., Qiu, H., Tan, Z., Liu, Y., Ma, J., Wang, X.: Resolving data sparsity by multi-type auxiliary implicit feedback for recommender systems. Knowl. Based Syst. 138, 202–207 (2017)CrossRef

Hofmann, T.: Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. 22(1), 89–115 (2004)CrossRef

Jriji, D., Krichen, S., Madany, F.: A memetic algorithm for the tourist trip design with clustered points of interests. In: 2020 International Multi-Conference on: “Organization of Knowledge and Advanced Technologies” (OCTA), pp. 1–6 (2020)

Kabassi, K.: Personalizing recommendations for tourists. Telemat. Inform. 27(1), 51–66 (2010)CrossRef

Kinoshita, T., Nagata, M., Shibata, N., Murata, Y., Yasumoto, K., Ito, M.: A personal navigation system for sightseeing across multiple days. In: Proceedings of the 3rd International Conference on Mobile Computing and Ubiquitous Networking (ICMU 2006), pp. 254–259 (2006)

Kontogianni, A., Kabassi, K., Virvou, M., Alepis, E.: Smart tourism through social network user modeling: a literature review. In: 2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA). IEEE, pp. 1–4 (2018)

Kotkov, D., Wang, S., Veijalainen, J.: A survey of serendipity in recommender systems. Knowl. Based Syst. 111, 180–192 (2016)CrossRef

Kinnear, K. E.: Advances in genetic programming, vol. 1. MIT Press (1994)

Lorenzi, F., Loh, S., Abel, M.: Personal tour: a recommender system for travel packages. In: 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology. IEEE, pp. 333–336 (2011)

Macskassy, S., Provost, F.: Classification in networked data: a toolkit and a univariate case study. J. Mach. Learn. Res. 8, 935–983 (2007)

Mariani, M., Baggio, R., Fuchs, M., Höepken, W.: Business intelligence and big data in hospitality and tourism: a systematic literature review. Int. J. Contemp. Hosp. Manag. 30, 3514–3554 (2018)CrossRef

Maruyama, A., Shibata, N., Murata, Y., Yasumoto, K., Ito, M.: P-tour: a personal navigation system for tourism. In: Proceedings of 11th World Congress on ITS, pp. 18–21 (2004)

Moreno, A., Valls, A., Isern, D., Marin, L., BorríS, J.: Sigtur/e-destination: ontology-based personalized recommendation of tourism and leisure activities. Eng. Appl. Artif. Intell. 26(1), 633–651 (2013)CrossRef

Nemade, G., Deshmane, R., Thakare, P., Patil, M., Thombre, V.D.: Smart tourism recommender system. Int. Res. J. Eng. Technol. (IRJET) 4(11), 601–603 (2017)

Nguyen, H., Richards, R., Chan, C.C., Liszka, K.J.: RedTweet: recommendation engine for reddit. J. Intell. Inf. Syst. 47(2), 247–265 (2016)CrossRef

Nilashi, M., Dalvi-Esfahani, M., Roudbaraki, M.Z., Ramayah, T., Ibrahim, O.: A multi-criteria collaborative filtering recommender system using clustering and regression techniques. J. Soft Comput. Decis. Support Syst. 3(5), 24–30 (2016)

Noor, N.M.M., Ahm, I.A., Ali, N.H., Ismail. F.: Intelligent Decision Support System for Tourism Destination Choice: A Preliminary Study. International Symposium on Information Technology, Kuala Lumpur (2010)

Pan, W.: A survey of transfer learning for collaborative recommendation with auxiliary data. Neurocomputing 177, 447–453 (2016)CrossRef

Pazzani, M.J., Billsus, D.: Content-Based Recommendation Systems. The Adaptive Web, pp. 325–341. Springer, Berlin (2007)

Pecli, A., Giovanini, B., Pacheco, C.C., Moreira, C., Ferreira, F., Tosta, F., Tesolin, J., Dias, M.V., Filho, S., Cavalcanti, M.C., Goldschmidt, R.: Dimensionality reduction for supervised learning in link prediction problems. In: Proceedings of the 17th International Conference on Enterprise Information Systems, SCITEPRESS—Science and and Technology Publications, pp. 295–302 (2015)

Power, D.: What is a DSS? Online Executive J. Data-Intensive Decis. Support 1(3), 223–232 (1997)

Power, D.J.: Decision Support Systems: Concepts and Resources for Managers. Quorum Books, Westport (2002)

Pozzi, F.A., Fersini, E., Messina, E.: Bayesian model averaging and model selection for polarity classification. In: International Conference on Application of Natural Language to Information Systems. Springer, pp. 189–200 (2013)

Pozzi, F.A., Fersini, E., Messina, E., Liu, B.: Sentiment Analysis in Social Networks. Morgan Kaufmann, Boston (2016)

Pronoza, E., Yagunova, E., Volskaya, S.: Aspect-based restaurant information extraction for the recommendation system. In: Human Language Technology. Challenges for Computer Science and Linguistics. Springer, pp. 371–385 (2016)

Ruotsalo, T., Haav, K., Stoyanov, A., Roche, S., Fani, E., Deliai, R., MäKelä, E., Kauppinen, T., HyvöNen, E.: SmartMuseum: a mobile recommender system for the web of data. Web Semant. 20, 50–67 (2013)CrossRef

Sana, A.A., Philips, J., Tabrizi, N.: Current trends in collaborative filtering recommendation systems. In: Xia, Y., Zhang, L.J. (eds.) Services–SERVICES 2019 Lecture Notes in Computer Science, vol. 11517, pp. 46–60. Springer, Cham (2019)

Santiago, F.M., López, F.A., Montejo-Ráez, A., López, A.U.: GeOasis: a knowledge-based geo-referenced tourist assistant. Expert Syst. Appl. 39(14), 11737–11745 (2012)CrossRef

Sebastia, L., Garcia, I., Onaindia, E., Guzman, C.: e-Tourism: a tourist recommendation and planning application. In: Proceedings of the 20th Institute of Electrical and Electronics Engineers (IEEE). International Conference on Tools with Artificial Intelligence (ICTAI), vol. 2, pp. 89–96 (2008)

Souffriau, W., Vansteenwegen, P.: (2010) Tourist trip planning functionalities: state-of-the-art and future. In: Daniel, F., Facca, F.M. (eds.) Current Trends in Web Engineering ICWE: Lecture Notes in Computer Science. Springer, Berlin (2010)

Verma, C., Hart, M., Bhatkar, S., Parker-Wood, A., Dey, S.: Improving scalability of personalized recommendation systems for enterprise knowledge workers. IEEE Access 4, 204–215 (2016)CrossRef

Yin, Z., Yueting, Z., Jiangqin, W., Liang, Z.: Applying probabilistic latent semantic analysis to multi-criteria recommender system. AI Commun. 22(2), 97–107 (2009)CrossRef

Zhai, H., Li, J.: Refine social relations and differentiate the same friends’ influence in recommender system. In: Mining Intelligence and Knowledge Exploration. Springer, pp. 504–514 (2015)

Title: Exploiting social data for tourism management: the SMARTCAL project
Authors: Annarita De Maio
Elisabetta Fersini
Enza Messina
Francesco Santoro
Antonio Violi
Publication date: 06-10-2020
Publisher: Springer Netherlands
Published in: Quality & Quantity / Issue Special Issue 3/2023
Print ISSN: 0033-5177
Electronic ISSN: 1573-7845
DOI: https://doi.org/10.1007/s11135-020-01049-8

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Other articles of this Special Issue 3/2023

Emergency management and internal audit of emergency preparedness of pre-hospital emergency care

Political segmentation based on pictorial preferences on social media

AnnuityRIR: an R-package to approximate the value of an annuity according to the non-central moments of the capitalization factor

Illusion of prediction possibility of random outcomes: experimental results

Investigating financial statements in hospitality: a quantitative approach

Outcomes from a visitors study at the “INGV Open Day Event”