Intermediate results processing for aggregated SPARQL queries

Aggregated search approach in the web of data is to look for results of a single query by aggregating pieces of data from distributed data sources and integrating them, if possible, into an entire entity. However, it may be possible that some parts of the query return null results which affects answers processing. In this work, we propose a star-group patterns-based solution to prepare a SPARQL query to be executed over distributed data sources without having prior knowledge of contributing data sources. The first objective of this work is identifying the complementarity between query parts after decomposing it, and the second one is rewriting the user's query considering only parts with not null results based on star-group patterns in order to return semantically significant answers. The evaluation of our proposed solution shows that this query rewriting method allows to return as much as possible the sought information.