Building Summary Graphs of RDF Data in Semantic Web

The structured data available in the semantic web have been rapidly increasing with the contribution of linked open data and other similar community initiatives in recent years. Thus, searching and processing large data have become more challenging. Building a summary graph can help reduce the computational complexity and query time in semantic searches by providing an intermediate index structure which contains entity type classes and relations between them. In the current study, we propose an algorithm for discovering the types of entities in RDF data and for building a summary graph structure for faster computational processing.