Dynamic Adaptation of Personalised Recommendations Based on Tourists Affective State

@Article {
author = {Petr Aksenov, Andrés Navarro García, David Oyarzun Laura, Theo Arentze, Astrid Kemperman},
title = {Dynamic Adaptation of Personalised Recommendations Based on Tourists Affective State},
pages = {491-496},
volume = {529},
keywds = {

Affective Computing, Emotions, Recommendation, Tourism, Utility

}
abstract = {

The presented work in progress is on the inclusion of information about tourists’ emotions in personalising their cultural program recommendations. Emotions are estimated unobtrusively and in real time from facial expressions during tourists’ interaction with a dedicated 3D- and AR-based application for cultural tourism. The affective data so collected is used for creating an affective map of an area, where each attraction (point of interest) is assigned an affective score in accordance with the involved affective model. The main goal of our work is to use these affective scores in determining and recommending attractions and activities which suit, among other criteria, the tourist’s current or desired affective state.

}
isbn = {978-3-319-21383-5},
date = {2015-08-02},
year = {2015},
}