Autre
Big data integration: A semantic mediation architecture using summary
Aicha Aggoune, Abdelkrim Bouramoul, Mohamed Khireddine Kholladi
Résumé
This paper presents our semantic mediation architecture for homogeneously retrieving data from big data. The architecture is split into three layers to find relevant answers of this data. In the proposed ontology-based approach, we use our domain ontology on alimentation risks field as well as a global schema of mediator and we apply the summarization process based on ontology for describes part of the data set. Thus, the auto evolution of ontology is based on this huge amount of data. The research of answer is related to relevant summaries which represent high-level semantics.
Détails
| Langue originale | English |
|---|---|
| Événement | International Conference on Advanced Technologies for Signal and Image Processing |
| Volume | 458 |
| Numéro d’article | 7523044 |
| Pages | 21-25 |
| DOI | 10.1109/atsip.2016.7523044 |
| Statut de publication | Publié — 1 mars 2016 |
Mots-clés
Empreinte
- Semantic Web and Ontologies
- Biomedical Text Mining and Ontologies
- Innovation in Digital Healthcare Systems
- semantic mediation
- big data integration
- ontology-based data access
- ontology evolution
- Artificial Intelligence
- Molecular Biology
- Health Information Management
- Computer Science
- Biochemistry, Genetics and Molecular Biology
- Health Professions