Knowledge representation and management based on an ontological CBR system for dementia caregiving

Abstract

Case-based reasoning (CBR) is a problem-solving methodology that uses past knowledge and experiences to interpret or solve new problems. It is appropriate for experience-based repeatable problems. This article describes a method for managing the semantic consistency of an ontology of dementia caregiving as an ontological CBR system. Ontologies are used for our knowledge model and case representation for creating our case base. Using international classification of functioning, disability, and health (ICF) from world health organization (WHO) report, a dementia ontology such as ADO and a systematic review of quantitative and qualitative studies about the needs of informal caregivers in this related diseases enhances the development and integration of our recommender system. It is a caregiver support tool to Detect and Predict dementia using information of carings Tasks by Ontological Case-based Learning Assistant System, called DePicT Dementia Onto-CLASS. This paper proposes an ontological CBR system by utilizing protégé and myCBR open source tools. Representing CBR knowledge using this ontology and building a case retrieval algorithm improves the accuracy of resulting systems. Moreover, the representation of dependencies among concepts and relationships can assist caregivers in certifying the semantic consistency of this ontology. The ontology evaluated with Hermit and myCBR, and caregivers validated the obtained results.