2011
DOI: 10.1016/j.knosys.2011.01.002
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An ontology-based universal design knowledge support system

Abstract: Cataloged from PDF version of article.An effective and efficient knowledge support system is crucial for universal design process, as it has become a major design issue in the last decade with the growth of the elderly population and disabled people. There are a limited number of CAD investigations on the nature of knowledge processing that supports the cognitive activities of universal design process. Therefore, this paper proposes an ontology-based computer-assisted universal design (CAUD) plug-in tool that … Show more

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Cited by 53 publications
(21 citation statements)
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References 39 publications
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“…However, designing effective tutoring strategies from learners' data requires numerous language learners with a variety of cognitive and affective factors (e.g., proficiency level, age, gender, mood, and concentration) [8], which is usually very expensive and timeconsuming even with design support systems [1].…”
Section: Language Learner Simulation To Learn Effective Tutoring Stramentioning
confidence: 99%
“…However, designing effective tutoring strategies from learners' data requires numerous language learners with a variety of cognitive and affective factors (e.g., proficiency level, age, gender, mood, and concentration) [8], which is usually very expensive and timeconsuming even with design support systems [1].…”
Section: Language Learner Simulation To Learn Effective Tutoring Stramentioning
confidence: 99%
“…Although there is a general lack of knowledge how designers achieve solutions, they should operate an effective strategy to increase the possibility of creating promising concepts as early as possible (Afacan and Demirkan, 2011). Analyzing interior environmental quality raises a number of methodological difficulties involving correlated qualitative and quantitative variables.…”
Section: Morphological Analysismentioning
confidence: 99%
“…Using a grid box, the technique of cross consistency assessment (CCA) reduces the number of possible solutions by eliminating illogical solution combinations (Afacan and Demirkan, 2011;Ritchey, 2006). This method is based on the insight that there may be numerous pairs of conditions in the morphological field that are mutually incompatible.…”
Section: Cross-consistency Assessmentsmentioning
confidence: 99%
“…To express the semantic information of knowledge to ensure that the knowledge is comprehensible to either humans or machines [1,3], domain ontology is constructed to annotate the knowledge to specify the knowledge domain. The complexity of the ontology model will increase dramatically with the increase of covering areas.…”
Section: Construction Of Domain Ontologymentioning
confidence: 99%