Supporting people with autism spectrum disorders in the exploration of PoIs: An Inclusive Recommender System

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.