Automatic approach to enrich databases using ontology: Application in medical domain
Author(s) -
Zikhla,
Kaouther Nouira
Publication year - 2017
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2017.08.221
Subject(s) - computer science , database , ontology , consistency (knowledge bases) , information retrieval , domain (mathematical analysis) , set (abstract data type) , data mining , volume (thermodynamics) , artificial intelligence , mathematical analysis , philosophy , mathematics , epistemology , physics , quantum mechanics , programming language
The enrichment of databases is fundamental to maintain them, as well as the consistency and accuracy of the data. The database becomes useless if it is not up to date. Since there are a large number of databases, an automatic enrichment approach is required. However, until now no efficient approach has been provided in order to cope with this problem. In this paper, we propose a new approach to automate the enrichment of databases. It is based on an ontology, which model domains through sets of concepts and semantic relationships established between them. The proposed approach presents a set of rules to analyze ontologies and databases components and filter subsequently the necessary ones for the database enrichment of databases. We applied our approach in the medical domain that is a renewable domain. Also, it is characterized by a large number of databases and ontologies, and a large volume of data. For experimentations, a platform is developed to test rules using medical databases and medical ontologies. As a result we obtain enriched databases with new components that are either tables, attributes, or records.
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