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Activity qualifiers using an argument-based construction
Umeå University, Faculty of Science and Technology, Department of Computing Science. (User Interaction and Knowledge Modelling)ORCID iD: 0000-0002-6035-800X
Umeå University, Faculty of Science and Technology, Department of Computing Science.
Umeå University, Faculty of Medicine, Department of Community Medicine and Rehabilitation, Physiotherapy.
Umeå University, Faculty of Science and Technology, Department of Computing Science.
2018 (English)In: Knowledge and Information Systems, ISSN 0219-1377, E-ISSN 0219-3116, Vol. 54, no 3, p. 633-658Article in journal (Refereed) Published
Abstract [en]

Based on an argumentation theory approach, we present a novel method for evaluating complex goal-based activities by generalizing a notion of qualifier defined in the health domain. Three instances of the general qualifier are proposed: Performance, Actuation and Capacity; the first one evaluates what a person does, the second how an individual follows an action plan, and the third one how "well" or "bad" an activity is executed. Qualifiers are intended to be used by autonomous systems for evaluating human activity. We exemplify our approach using a health domain assessment protocol. Main results of this test show a partial correlation between ambiguities assessed by experts and our argument-based approach; and a multi-dimensional perspective how an activity is executed when a combined evaluation of qualifiers is used. This last outcome was interesting for some therapists consulted. Results also show differences between values of qualifiers using different argumentation semantics; two scenarios were proposed by therapist for using different semantics: preliminary activity screening and time-span follow-up evaluation.

Place, publisher, year, edition, pages
Springer, 2018. Vol. 54, no 3, p. 633-658
Keywords [en]
Human activity, Argumentation theory, Logic programming, Performance Capacity, Activity evaluation
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-141040DOI: 10.1007/s10115-017-1112-7ISI: 000425010800006OAI: oai:DiVA.org:umu-141040DiVA, id: diva2:1151200
Available from: 2017-10-23 Created: 2017-10-23 Last updated: 2018-06-09Bibliographically approved

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Guerrero, EstebanNieves, Juan CarlosSandlund, MarleneLindgren, Helena
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CiteExportLink to record
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