Big data: Methods, prospects, techniques

Abstract

Nowadays, Web content knows a rapid increase in syntactic data that makes their processing and storage difficult in classical systems. An alternative approach is to represent the Web in a more understandable form by the machines based on the initiative of the semantic web, on the new technologies and algorithms existing in parallelism, cloud computing, distributed systems and big data mining. These new intelligent techniques allow us to give new representations to the sources of the Web. Our research will develop around the semantic search of information on a set of massive, distributed, autonomous and heterogeneous Resource Description Framework (RDF) data. However, only a representation format of knowledge for their semantic access is not sufficient and we need strong response mechanisms to efficiently handle global and distributed queries on a set of RDF data marked by the dynamics and scalability of their content.