P Petr Aksenov

C-space: Fostering new creative paradigms based on recording and sharing “casual” videos through the internet

A key theme in ubiquitous computing is to create smart environments in which there is seamless integration of people, information, and physical reality. In this manuscript, we describe a set of tools that facilitate the creation of such environments, e,g, a service to transform videos recorded with mobile devices into navigable 3D scenes, a service to compute and describe the emotional processes that occur during the user interaction with such content, a service that takes into account certain dynamic needs of users in personalizing solutions for allocating their leisure time and activities, a gamified crowdsourcing application, and a set of projection-based tools for creating and interacting with augmented environments. Ultimately, our objective is have a framework that seamless integrates all these components, to foster creativity processes.

A Personalised Recommender System for Tourists on City Trips: Concepts and Implementation

In this paper we introduce a new recommender system for urban tourists. The goal of the system is to enrich tourists’ experience by offering them personalised tour recommendations tailored to their dynamic user profiles. Particular attention in the proposed approach is paid to the influence of basic leisure needs of an individual, which include new experiences, entertainment, being in open area, relaxation, physical exercise, and socialising, on the tour composition. These needs tend to be dynamic and give rise to saturation effects and variety seeking behaviour. The system is developed as part of the larger c-Space framework, in which a number of technologies, such as projective augmented reality, a newly proposed near real-time 4D dynamic scene reconstruction, and affective computing, are brought together and used to enrich experiences of users in their interactions with built environments. The paper describes the main concepts of the recommender system and its implementation in the specified context of the city of Trento, Italy.

Estimating a latent-class user model for travel recommender systems

In determining the selection of sites to visit on a trip tourists have to trade-off attraction values against routing and time-use characteristics of points of interest (POIs). For recommending optimal personalized travel plans an accurate assessment of how users make these trade-offs is important. In this paper we report the results of a study conducted to estimate a user model for travel recommender systems. The proposed model is part of c-Space—a tour-recommender system for tourists on a city trip which uses the LATUS algorithm to find personalized optimal tours. The model takes into account a multi-attribute utility function of POIs as well as dynamic needs of persons on a trip. A stated choice experiment is designed where the current need is manipulated as a context variable and activity choice alternatives are varied. A random sample of 316 individuals participated in the on-line survey. A latent-class analysis shows that significant differences exist between tourists in terms of how they make the trade-offs between the factors and respond to needs. The estimation results provide the parameters of a multi-class user model that can be used for travel recommender systems.

Dynamic Adaptation of Personalised Recommendations Based on Tourists’ Affective State

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.