Authors:
Vivien Guillet
1
;
Beatrice Rumpler
2
and
Jean-Marie Pinon
2
Affiliations:
1
LIRIS-INSA CNRS FRE 2672 - INSA; EO-EDPS, France
;
2
LIRIS-INSA CNRS FRE 2672 - INSA, France
Keyword(s):
Adaptation, guidance, user modeling, stereotype, impairement
Related
Ontology
Subjects/Areas/Topics:
Accessibility to Disabled Users
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Computer-Supported Education
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Human-Computer Interaction
;
Information Systems Analysis and Specification
;
Intelligent User Interfaces
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Society, e-Business and e-Government
;
Ubiquitous Learning
;
User Needs
;
Verification and Validation of Knowledge-Based Systems
;
Web Information Systems and Technologies
Abstract:
Among today’s emerging pedestrian guidance systems (i.e. able to automatically answer questions of the form “How should I go from localization a to localization b ?), some are dedicated to blind people; fewer if any focus on impaired people as well as people without any deficiency. Contrary to this, the “ouvej” system relies on representing impairments as a part of the user’s profile in order to be adaptable to any kind of user. Furthermore, we consider that benefits of the user modeling involved in such adaptation mechanisms go beyond the only impairment category in order to respect the user’s preferences in itineraries and itineraries descriptions, by modeling itinerary environment. Whereas existing adaptive system often rely on the use of explicit feedback from the user, we propose to limit adaptation-related interactions by using implicit user evaluations inferred from observations of users interactions with the system. This article focuses on blind pedestrian users using a vocal
interface. After detailing our approach, we detail our itinerary and user models; Then the implicit as well as explicit itinerary evaluation mechanisms are described; Next sections focus on the actual adaptation and expected benefits of inferences between different users; Our prototype is then described. We conclude by presenting our first observations, future work and evaluation.
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