Abstract
In an era facing data and information explosion, there is a demanding need to filter and adapt the content presented to users while interacting with mobile applications. Offering a personalized User Experience (UX) seems to be extremely important in a Smart Tourism-Destination App concept too, in order to enrich tourist experience and also to make a destination more competitive. The main objective of this paper is to present how user modeling could be accomplished via data originating from users’ social networks, where various aspects of their personality are collected and profiled, as well as data collected from their smartphones implicitly, requiring no user interaction. The data collected by the user model are further processed using a multi-criteria decision making theory called Analytic Hierarchy Process (AHP) in order to select the touristic destination that seems to be the best for the user interacting with the mobile application.
This work has been partly supported by the University of Piraeus Research Center.
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References
Fidas, C.A., Avouris, N.M.: Personalization of mobile applications in cultural heritage environments. In: 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA). https://doi.org/10.1109/IISA.2015.7388114
Bhargava, P., Agrawala, A.K.: Modeling users’ behavior from large scale smartphone data collection. EAI Endorsed Trans. Context.-Aware Syst. Appl. 3(10), e3 (2016). https://doi.org/10.4108/eai.12-9-2016.151677
Yin, H., Cui, B., Chen, L., Hu, Z., Zhou, X.: Dynamic user modeling in social media systems. ACM Trans. Inf. Syst. 33(3), article 10, 44 pages (2015). https://doi.org/10.1145/2699670
Liu, X., Aberer, K.: SoCo: a social network aided context-aware recommender system. In: Proceedings of the 22nd International Conference on World Wide Web (WWW 2013), pp. 781–802. ACM, New York (2013). https://doi.org/10.1145/2488388.2488457
Yus, R., Pappachan, P.: Are apps going semantic? A systematic review of semantic mobile applications. In: Conference: 1st International Workshop on Mobile Deployment of Semantic Technologies (MoDeST 2015), Co-located with the 14th International Semantic Web Conference (ISWC 2015), Bethlehem, PA, USA (2015)
Kobsa, A., Wahlster, W.: User Models in Dialog Systems. Springer, Heidelberg (1989). https://doi.org/10.1007/978-3-642-83230-7
Otebolaku, A.M., Andrade, M.T.: User context recognition using smartphone sensors and classification models. J. Netw. Comput. Appl. 66, 33–51 (2016). https://doi.org/10.1016/j.jnca.2016.03.013
Papatheocharous, E., Belk, M., Germanakos, P., Samaras, G.: Towards implicit user modeling based on artificial intelligence, cognitive styles and web interaction data. Int. J. Artif. Intell. Tools 23(2) (2014). https://doi.org/10.1142/S0218213014400090
Fan, W., Gordon, M.D.: The power of social media analytics. Commun. ACM 57(6), 74–81 (2014). https://doi.org/10.1145/2602574
Saaty, T.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980)
Zhu, Y., Buchman, A.: Evaluating and selecting web sources as external information resources of a data warehouse. In: The Third International Conference on Web Information Systems Engineering (WISE 2000), pp. 149–160 (2000)
Tiwari, N.: Using the Analytic Hierarchy Process (AHP) to identify performance scenarios for enterprise application. Computer Measurement Group. Measure It, vol. 4(3) (2006)
Virvou, M., Alepis, E.: Mobile educational features in authoring tools for personalised tutoring. Comput. Educ. 44(1), 53–68 (2005). https://doi.org/10.1016/j.compedu.2003.12.020
Yrr, O., Liu, C.H., Sheng, Z., Leung, V.C.M., Moreno, W., Leung, K.K.: Context-awareness for mobile sensing: a survey and future directions. IEEE Commun. Surv. Tutor. 18(1), 68–93 (2016). https://doi.org/10.1109/COMST.2014.2381246
Hofer, T., Schwinger, W., Pichler, M., Leonhartsberger, G., Altmann, J., Retschitzegger, W.: Context-awareness on mobile devices - the hydrogen approach. In: Proceedings of the 36th Annual Hawaii International Conference on System Sciences, 10 pp. (2003). https://doi.org/10.1109/HICSS.2003.1174831
Kim, H.R., Chan, P.K.: Learning implicit user interest hierarchy for context in personalization. In: Proceedings of the 8th International Conference on Intelligent User Interfaces (IUI 2003), pp. 101–108. ACM, New York (2003). https://doi.org/10.1145/604045.604064
Siraj, S., Mikhailov, L., Keane, J.A.: PriEsT: an interactive decision support tool to estimate priorities from pairwise comparison judgments. Intl. Trans. Op. Res. 22, 217–235 (2015). https://doi.org/10.1111/itor.12054
Vincke, P.: Multicriteria Decision-Aid. Wiley, Chichester (1992)
Global social media research summary (2018). https://www.smartinsights.com/social-media-marketing/social-media-strategy/new-global-social-media-research/. Accessed 30 Mar 2018
Social media - Statistics & Facts. https://www.statista.com/topics/1164/social-networks/. Accessed 30 Mar 2018
LoginManager class. https://developers.facebook.com/docs/reference/android/current/class/LoginManager/. Accessed 19 Apr 2018
Facebook SDK. https://developers.facebook.com/docs/android/getting-started/. Accessed 16 Apr 2018
Facebook Permissions. https://developers.facebook.com/docs/facebook-login/android/permissions. Accessed 18 Apr 2018
Facebook Graph Api Explorer. https://developers.facebook.com/tools/explorer/. Accessed 18 Apr 2018
https://developers.facebook.com/docs/graph-api/using-graph-api/#fieldexpansion. Accessed 20 Apr 2018
Graph Api Overview. https://developers.facebook.com/docs/graph-api/overview. Accessed 20 Apr 2018
All Facebook Categories. https://developers.facebook.com/tools/explorer/314199319068817?method=GET&path=fb_page_categories&version=v2.12. Accessed 20 Apr 2018
WikiData overview. https://www.wikidata.org/wiki/Wikidata:Main_Page. Accessed 20 Apr 2018
Wikidata Introduction. https://www.wikidata.org/wiki/Wikidata:Introduction. Accessed 20 Apr 2018
The Generation Z Study of Tech Intimates. https://www.commscope.com/Insights/. Accessed 23 Apr 2018
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Kontogianni, A., Kabassi, K., Alepis, E. (2018). Designing a Smart Tourism Mobile Application: User Modelling Through Social Networks’ User Implicit Data. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11186. Springer, Cham. https://doi.org/10.1007/978-3-030-01159-8_14
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