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User Context Ontology for Adaptive Mobile-Phone Interfaces
- Source :
- IEEE Access, Vol 9, Pp 96751-96762 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- The Adaptive User Interface (AUI) adapts to the changes in the context of use and provides improved interaction abilities for different users. The adaptivity in the user interfaces requires in depth knowledge of context. There is a need to enrich user profiles to achieve the personalized services with the ability to adapt the user’s context. The context can be reflected in a particular kind of knowledge and hence modeled as ontology. Ontology based context models are effective means to handle complex situations that support the sharing or integration of context information. This paper presents ontology based context model using OWL for adaptive mobile devices. It models the context over its four major elements including device, user, environment (location and time) and activity. The proposed ontology was derived in different classes, relationships, associations, dependencies and constraints to model dynamic context. Ontologies present a standardized, consistent and shareable context model. The context model and consequent context snapshots can be acknowledged by AUI to present a suitable user interface. The ontology was developed using Protégé on the basis of each context type having different values. Semantic querying (SPARQL) was used for knowledge acquisition. Moreover, the Pellet and HermiT Reasoner were used to verify the rules, relations and constraints to avoid the inconsistency between classes. Comparative to other context models for adaptive interfaces, ontological model provides more of scalability and growth with learning new context in to the shared context knowledge.
- Subjects :
- Context model
General Computer Science
Computer science
knowledge representation
General Engineering
Context (language use)
Semantic reasoner
Protégé
Ontology (information science)
Knowledge acquisition
TK1-9971
Adaptive user interface
Human–computer interaction
context aware interface
General Materials Science
Electrical engineering. Electronics. Nuclear engineering
User interface
ontology driven interfaces
knowledge engineering
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....a1edc555affab579cd302f17f50fedb4