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.