RDF triple processing methodology for the recommendation system using personal information

Abstract

In this paper, we design and implement the personalized recommend system that provides more semantic information to users using the RDF triples and personal information. The system consists of the data storage, information search module, document collection module, data merge module and recommend module. These new modules are different from the existing modules that have been using in the current Web. These new modules are suitable for the semantic Web environment. Especially, in this paper, we focus on the RDF that is one of the ontology languages. And all modules are newly designed for processing the RDF triple. Finally, we have the test to give the necessity of our study in the virtual semantic Web environment.