Global similarity based ontology to enhance the quality of big and distributed RDF data

Autor: Ghadi Abderrahim, Lamrani Kaoutar
Rok vydání: 2019
Předmět:
Zdroj: SCA
DOI: 10.1145/3368756.3369092
Popis: Nowadays, the web content of e-commerce data is increasing rapidly, which make the traditional techniques to querying this resources not efficient, for that the researches focus to how using the new technologies to provide a relevant and complete answers to user query. Using Technologies of big data and web semantic are two new fields that can be exploiting to processes data semantically and to handle with storage of this hug data. In recent works [1, 2], we have proposed the techniques using in big data and we are proposed in architecture that integrate the big RDF (Resources Description Framework) data semantically by exploiting HDFS (Hadoop Distributed File System) to store Global RDF schema and Map Reduce to process the query, in aims to give an infrastructure who give a complete and pertinent answers to user query. In this paper we are proposed a simple scenario to have a complete and pertinent response to user query.
Databáze: OpenAIRE