Personalized Tourist Guide for People with Autism

Cena, Federica; Mauro, Noemi; Ardissono, Liliana; Mattutino, Claudio; Rapp, Amon; Cocomazzi, Stefano; Brighenti, Stefania; Keller, Roberto

doi:10.1145/3386392.3399280

Cited by 9 publications

(6 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The result of this project is a mobile app that manages dynamic geographical maps specifically conceived for users with autism spectrum disorders, but which target neurotypical people, as well. 3 The remainder of this paper is organized as follows: first, we discuss the spatial needs of autistic people (Section 2), and we position our work in the related one (Section 3). Section 4 outlines how we gather data about users and PoIs, and Section 5 presents our model.…”

Section: Related Workmentioning

confidence: 99%

Supporting people with autism spectrum disorders in the exploration of PoIs

2022

Self Cite

View full text Add to dashboard Cite

The suggestion of Points of Interest (PoIs) to people with autism spectrum disorders challenges the research about recommender systems by introducing an explicit need to consider both user preferences and aversions in item evaluation. The reason is that autistic users' perception of places is influenced by sensory aversions, which can cause stress and anxiety when they visit the suggested PoIs. Therefore, the management of individual preferences is not enough to provide these people with suitable recommendations. To address this issue, we propose a Top-N recommendation model that combines information about the user's idiosyncratic aversions with her/his preferences in a personalized way. The goal is that of suggesting the places that (s)he can like and smoothly experience at the same time. We are interested in finding a user-specific balance of compatibility and interest within a recommendation model that integrates heterogeneous evaluation criteria to appropriately take these aspects into account. We tested our model on 148 adults, 20 of which were people with autism spectrum disorders. The evaluation results show that, on both groups, our model achieves superior accuracy and ranking results than the recommender systems based on item compatibility, on user preferences, or which integrate these aspects using a uniform evaluation model. These findings encourage us to use our model as a basis for the development of inclusive recommender systems.

show abstract

Section: Related Workmentioning

confidence: 99%

Supporting people with autism spectrum disorders in the exploration of PoIs

2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…Currently, we are integrating the approach described in this paper into the PIUMA mobile guide (Cena et al, 2020(Cena et al, , 2021 which suggests places to visit to people with autism. We then plan to test our recommender systems in the field, by carrying out a user study with people from the Adult Autism Center of Torino.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Using consumer feedback from location-based services in PoI recommender systems for people with autism

Mauro

Ardissono

Cocomazzi

et al. 2022

Expert Systems with Applications

Self Cite

View full text Add to dashboard Cite

“…Personalized travel guides, such as those described in [6,7,20], suggest places and/or events by analyzing the user's interests in item categories (e.g., cinemas or parks), as well as her/his preferences for specific item features, such as the types of artwork exposed in a museum. Moreover, some inclusive recommender systems, like PIUMA [8,23] and INTRIGUE [3], examine sensory or accessibility features of items to guarantee that the user can smoothly experience the suggested places. In all such cases, the only evaluated entity is the item itself, whose features are matched to the preferences of the target user in order to estimate its suitability.…”

Section: Related Work 21 Recommender Systemsmentioning

confidence: 99%

Beyond Traditional Cultural Heritage Recommender Systems: Suggesting Airbnb Experiences to Users

Mauro

Ardissono

Petrone

et al. 2021

Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization

Self Cite

View full text Add to dashboard Cite

Traditional recommender systems suggest Cultural and Natural Heritage items to visitors by matching the target user to the available options, one-to-one. However, the increasing diffusion of informal activities and events, supported by location-based services such as Airbnb, extends personalized recommendation to a manyto-one match-making task. Airbnb experiences, which any citizen can propose to offer geographic tours and thematic activities, are composed of at least two entities to be evaluated: the former is the experience itself (in terms of topic, cost, etc.); the latter is the host, who directly interacts with guests during the management of the planned activities. As both entities can dramatically influence guests' perceptions, they should be jointly taken into account by recommender systems. This paper presents our preliminary work aimed at extending the personalized suggestion of Cultural Heritage items to such composite objects. CCS CONCEPTS• Information systems → Web searching and information discovery; Recommender systems.

show abstract

Personalized Tourist Guide for People with Autism

Cited by 9 publications

References 22 publications

Supporting people with autism spectrum disorders in the exploration of PoIs

Supporting people with autism spectrum disorders in the exploration of PoIs

Using consumer feedback from location-based services in PoI recommender systems for people with autism

Beyond Traditional Cultural Heritage Recommender Systems: Suggesting Airbnb Experiences to Users

Contact Info

Product

Resources

About