Hybrid Index Structure based on MBB Approximation for Linked Data

Although a pragmatic approach towards achieving Semantic Web has gained some traction with Linked Data, there are still a lot of open problems in the area of Linked Data. Because Linked Data are modeled as RDF graphs, we cannot directly adopt existing solutions from database systems or Web technologies. This paper presents a hybrid method between the centralized approach and the distributed approach based on query processing to increase the join query performance. Using auxiliary indexes we can retrieve distributed data resources participating on a query result, rapidly reducing the amount of data that are really needed to be accessed on-demand. The performance of the proposed index structure is compared with some existing methods on a real RDF dataset. Our method outperforms the existing methods due to its ability to reduce a large amount of irrelevant resources.