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Supporting people with autism spectrum disorders in the exploration of PoIs: an inclusive recommender system

Authors:

Liliana Ardissono,

Federica CenaAuthors Info & Claims

Communications of the ACM, Volume 65, Issue 2

Pages 101 - 109

https://doi.org/10.1145/3505267

Published: 24 January 2022 Publication History

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Abstract

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.

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Cited By

Pera MCena FLandoni MMusto CStarke A(2024)Human Factors in User Modeling for Intelligent SystemsA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_1(3-42)Online publication date: 1-May-2024
https://doi.org/10.1007/978-3-031-55109-3_1
Felfernig AWundara MTran TPolat-Erdeniz SLubos SEl Mansi MGarber DLe V(2023)Recommender systems for sustainability: overview and research issuesFrontiers in Big Data10.3389/fdata.2023.12845116Online publication date: 30-Oct-2023
https://doi.org/10.3389/fdata.2023.1284511
Mauro NCena FPutnam CPera MRoldán Álvarez D(2023)Introduction to this special issue on intelligent systems for people with diverse cognitive abilitiesHuman–Computer Interaction10.1080/07370024.2023.225196939:1-2(1-7)Online publication date: 6-Sep-2023
https://doi.org/10.1080/07370024.2023.2251969
Show More Cited By

Index Terms

Supporting people with autism spectrum disorders in the exploration of PoIs: an inclusive recommender system
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
  2. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems
2. Social and professional topics
  1. User characteristics
    1. People with disabilities

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Published In

cover image Communications of the ACM

Communications of the ACM Volume 65, Issue 2

February 2022

110 pages

ISSN:0001-0782

EISSN:1557-7317

DOI:10.1145/3514042

Editor:
Andrew A. Chien
Association for Computing Machinery, New York, NY

Issue’s Table of Contents

Copyright © 2022 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 January 2022

Published in CACM Volume 65, Issue 2

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Cited By

Pera MCena FLandoni MMusto CStarke A(2024)Human Factors in User Modeling for Intelligent SystemsA Human-Centered Perspective of Intelligent Personalized Environments and Systems10.1007/978-3-031-55109-3_1(3-42)Online publication date: 1-May-2024
https://doi.org/10.1007/978-3-031-55109-3_1
Felfernig AWundara MTran TPolat-Erdeniz SLubos SEl Mansi MGarber DLe V(2023)Recommender systems for sustainability: overview and research issuesFrontiers in Big Data10.3389/fdata.2023.12845116Online publication date: 30-Oct-2023
https://doi.org/10.3389/fdata.2023.1284511
Mauro NCena FPutnam CPera MRoldán Álvarez D(2023)Introduction to this special issue on intelligent systems for people with diverse cognitive abilitiesHuman–Computer Interaction10.1080/07370024.2023.225196939:1-2(1-7)Online publication date: 6-Sep-2023
https://doi.org/10.1080/07370024.2023.2251969
Chang CZhou JWeng YZeng XWu ZWang CTang Y(2023)KGTN: Knowledge Graph Transformer Network for explainable multi-category item recommendationKnowledge-Based Systems10.1016/j.knosys.2023.110854278(110854)Online publication date: Oct-2023
https://doi.org/10.1016/j.knosys.2023.110854
Cena FMauro NRapp A(2023)How do sensory features of places impact on spatial exploration of people with autism? A user studyInformation Technology & Tourism10.1007/s40558-023-00244-125:1(105-132)Online publication date: 1-Mar-2023
https://doi.org/10.1007/s40558-023-00244-1
Mauro NArdissono LCocomazzi SCena F(2022)Using consumer feedback from location-based services in PoI recommender systems for people with autismExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.116972199:COnline publication date: 1-Aug-2022
https://dl.acm.org/doi/10.1016/j.eswa.2022.116972

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