Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments
| Autor: | Maricela Bravo, Josué Padilla-Cuevas, José Alejandro Reyes-Ortíz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
event enhancing
Ambient intelligence context reasoning event-driven representation Computer Networks and Communications Computer science Process (engineering) Event (computing) Knowledge engineering Representation (systemics) 020206 networking & telecommunications Context (language use) 02 engineering and technology Information technology T58.5-58.64 ontology model Human–computer interaction 0202 electrical engineering electronic engineering information engineering Ontology 020201 artificial intelligence & image processing Use case ComputingMethodologies_GENERAL knowledge engineering ComputingMilieux_MISCELLANEOUS |
| Zdroj: | Future Internet Volume 13 Issue 6 Future Internet, Vol 13, Iss 151, p 151 (2021) |
| ISSN: | 1999-5903 |
| DOI: | 10.3390/fi13060151 |
| Popis: | An Ambient Intelligence responds to user requests based on several contexts. A relevant context is related to what has happened in the ambient therefore, it focuses a primordial interest on events. These involve information about time, space, or people, which is significant for modeling the context. In this paper, we propose an event-driven approach for context representation based on an ontological model. This approach is extendable and adaptable for academic domains. Moreover, the ontological model to be proposed is used in reasoning and enrichment processes with the context event information. Our event-driven approach considers five contexts as a modular perspective in the model: Person, temporal (time), physical space (location), network (resources to acquire data from the ambient), and academic events. We carried out an evaluation process for the approach based on an ontological model focused on (a) the extensibility and adaptability of use case scenarios for events in an academic environment, (b) the level of reasoning by using competence questions related to events, (c) and the consistency and coherence in the proposed model. The evaluation process shows promising results for our event-driven approach for context representation based on the ontological model. |
| Databáze: | OpenAIRE |
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