Complex Relation Discovery from the Semantic Web

Abstract

The vision or the Semantic Web undertakes an extension or the current Web, in which machines can understand all the data. The nature of Semantic Web data is relationship-centric and is very complex. In this study we aimed to discover those complex but meaningful and concealed relationships between resource entities from the Semantic Web data. We utilized the notion of semantic relation discovery approach which aims to capture meaningful and probable complex relationships between entities in a dataset based on graph search model. We considered three fictitious datasets for the experiment. The outcome showed sequences and connections among the nodes and how the nodes are semantically inter-related.