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- Querying the Web of Data with Graph Theory-based Techniques + (The increasing amount of Linked Data on th … The increasing amount of Linked Data on the Web enables users to retrieve quality and complex information and to deploy innovative, added-value applications. The volume of available Linked Data and their spread across a large number of repositories make a strong case for ecient distributed SPARQL queries. However, in practice, current distributed SPARQL query processing techniques face issues on performance and scalability. In our previous work we provided initial evidence that graph theory-based techniques can address performance issues better than other approaches such as DARQ. Here we further exploit the potential of graph algorithms and we show how they can address performance and scalability for distributed SPARQL queries even better. To that end, we present an improved engine called GDS and we evaluate it by providing a detailed comparison to existing approaches for distributed queries (i.e. DARQ and FedX). By analyzing the evaluation results, we try to identify promising techniques for distributed SPARQL processing, and to outline the problems that need to be addressed in future research.t need to be addressed in future research.)
