Big data integration: A semantic mediation architecture using Summary

Abstract

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.