Abstract
Due to their complexity, tourism products present major challenges to recommender techniques. Especially the assessment of customer preferences in order to get accurate user profiles is a non-trivial task for several reasons: (a) tourism is an “emotional” experience, which is typically hard to capture by using rational terms; (b) particularly in early phases of a travel decision process, users are not able to explicitly express their preferences; (c) and they are often lacking domain knowledge and thus have difficulties to use the right terminology. In this paper we introduce an alternative, i.e., a picture-based approach, as a new method to implicitly elicit user preferences for tourism products. We develop a model in which a user’s travel profile is composed of seven basic factors. The scores of these factors are determined by asking the user to select a number of pictures that are appealing to him or her. The model as well as its implementation into a recommender system are described in detail. First evaluations show that interactions with the system are perceived as inspiring and enjoyable.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abdi H (2003) Factor rotations in factor analyses. In: Lewis-Beck M, Bryman AE, Liao TF (eds) Encyclopedia of social sciences research methods. Sage Publications, Thousand Oaks
Berger H, Denk M, Dittenbach M, Merkl D, Pesenhofer A (2007) Quo vadis homo turisticus? Towards a picture-based tourist profiler. Inf Commun Technol Tourism 2007:87–96
Borgatta EF (1964) A very short test of personality: the behavioral self-rating (BSR) form. Psychol Rep 14:275–284
Burke R, Ramezani M (2011) Matching recommendation technologies and domains. In: Recommender systems handbook. Springer, US, pp 367–386
Chen L, de Gemmis M, Felfernig A, Lops P, Ricci F, Semeraro G (2013) Human decision making and recommender systems. ACM Trans Interact Intell Syst (TiiS) 3(3):17
TUI.com GmbH (2013) TUI Reisewelten. http://www.tui.com/tui-reisewelten. Accessed July 2013
Conley JJ (1985) Longitudinal stability of personality traits: A multitrait-multimethod-multioccasion analysis. J Pers Soc Psychol 49:1266–1282
European Travel Commission (ETC) (2009) New media trendwatch. http://www.newmediatrend-watch.com. Accessed in 2010
Expedia, Inc (2013) Expedia. http://www.expedia.at. Accessed in September 2013
Garcia I, Sebastia L, Onaindia E (2011) On the design of individual and group recommender systems for tourism. Expert Syst Appl 38(6):7683–7692
Gibson H, Yiannakis A (2002) Tourist roles, needs and the lifecourse. Ann Tour Res 29:358–383
Goldberg LR (1993) The structure of phenotypic personality traits. Am Psychol 48:26–34
Gretzel U, Mitsche N, Hwang YH, Fesenmaier DR (2004) Tell me who you are and I will tell you where to go: use of travel personalities in destination recommendation systems. Inf Technol Tour 7(1):3–12
Hu R, Pu P (2010) A study on user perception of personality-based recommender systems. In: User modeling, adaptation, and personalization. Springer, Berlin Heidelberg, pp 291–302
John OP, Srivastava S (1999) The big-five trait taxonomy: history, measurement, and theoretical perspectives. Handb pers Theory Res 2(1999):102–138
Krinninger W (2012) Inspiration und information—kritische Erfolgsfaktoren von Reiseplatt-formen. In: Master’s thesis, Vienna University of Economics and Business
Lonely Planet (2013) Amex traveltype. http://www.lonelyplanet.com/campaigns/amex-traveltype. Accessed July 2013
McGinty L, Reilly J (2011) On the evolution of critiquing recommenders. In: Recommender systems handbook. Springer, USA, pp 419–453
Miniwatts Marketing Group (2013) Internet World Stats. http://www.internetworldstats.com. Accessed December 2013
Neidhardt J, Schuster R, Seyfang L, Werthner H (2014) Eliciting the users’ unknown preferences. In: Proceedings of the 8th ACM conference on recommender systems. ACM, USA
Pixtri OG (2013) PixMeAway. http://www.pixmeaway.com. Accessed December 2013
Poon A (1993) Tourism, technology and competitive strategies. CAB International, Wallingford
Ricci F (2002) Travel recommender systems. IEEE Intell Syst 17(6):55–57
Ricci F, Nguyen QN (2007) Acquiring and revising preferences in a critique-based mobile recommender system. Intell Syst IEEE 22(3):22–29
Ricci F, Woeber K, Zins A (2005) Recommendations by collaborative browsing. In: Information and communication technologies in tourism. Springer, pp 172–182
Ricci F, Rokach L, Shapira B (2011) Introduction to recommender systems handbook. In: Recommender systems handbook. Springer, US, pp 1–35
Schertler W, Schmid B, Tjoa AM, Werthner H (1994) Information and communication technologies in tourism. Springer, Wien
Sheldon PJ (1997) Tourism information technology. CAB International, UK
Trip Technologies Inc (2013) Tripbase travel your way. http://www.tripbase.com. Accessed September 2013
Werthner H, Klein S (1999) Information technology and tourism—a challenging relationship. Springer, Vienna
Werthner H, Ricci F (2004) E-commerce and tourism. Commun ACM 47(12):101–105
Werthner H, Stock O, Zancanaro M (2006) Futuring travel destination recommendation systems. Destination recommendation systems: behavioral foundations and applications. CAB International, London
Woszczynski AB, Roth PL, Segars AH (2002) Exploring the theoretical foundations of playfulness in computer interactions. Comput Hum Behav 18(4):369–388
Yiannakis A, Gibson H (1992) Roles tourists play. Ann Tour Res 19(2):287–303
Zins A (2007) Exploring travel information search behaviour beyond common frontiers. J Inf Technol Tour 9(3/4):149–164
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Neidhardt, J., Seyfang, L., Schuster, R. et al. A picture-based approach to recommender systems. Inf Technol Tourism 15, 49–69 (2015). https://doi.org/10.1007/s40558-014-0017-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40558-014-0017-5