Eliciting Touristic Profiles: A User Study on Picture Collections.

Authors: 
Mete Sertkan
Julia Neidhardt
Hannes Werthner
Type: 
Speech with proceedings
Proceedings: 
UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization
Publisher: 
Association for Computing Machinery, New York, NY, USA
Pages: 
230 - 238
ISBN: 
ISBN: 978-1-4503-6861-2
Year: 
2020
Abstract: 
Eliciting the preferences and needs of tourists is challenging, since people often have difficulties to explicitly express them, especially in the initial phase of travel planning. Recommender systems employed at the early stage of planning can therefore be very beneficial to the general satisfaction of a user. Previous studies have explored pictures as a tool of communication and as a way to implicitly deduce a traveller's preferences and needs. In this paper, we conduct a user study to verify previous claims and conceptual work on the feasibility of modelling travel interests from a selection of a user's pictures. We utilize fine-tuned convolutional neural networks to compute a vector representation of a picture, where each dimension corresponds to a travel behavioural pattern from the traditional Seven-Factor model. In our study, we followed strict privacy principles and did not save uploaded pictures after computing their vector representation. We aggregate the representations of the pictures of a user into a single user representation, ie, touristic profile, using different strategies. In our user study with 81 participants, we let users adjust the predicted touristic profile and confirm the usefulness of our approach. Our results show that given a collection of pictures the touristic profile of a user can be determined.
TU Focus: 
Information and Communication Technology
Reference: 

M. Sertkan, J. Neidhardt, H. Werthner:
"Eliciting Touristic Profiles: A User Study on Picture Collections.";
Vortrag: UMAP'20: 28th ACM Conference on User Modeling, Adaptation and Personalization, Genoa, Italy; 12.07.2020 - 18.07.2020; in: "UMAP '20: Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization", T. Kuflik, I. Torre, R. Burke, C. Gena (Hrg.); Association for Computing Machinery, New York, NY, USA, (2020), ISBN: 978-1-4503-6861-2; S. 230 - 238.

Zusätzliche Informationen

Last changed: 
09.01.2021 00:24:38
TU Id: 
294077
Accepted: 
Accepted
Invited: 
Department Focus: 
Business Informatics
Abstract German: 
Author List: 
M. Sertkan, J. Neidhardt, H. Werthner