SemLAV: Querying Deep Web and Linked Open Data with SPARQL

نویسندگان

  • Pauline Folz
  • Gabriela Montoya
  • Hala Skaf-Molli
  • Pascal Molli
  • Maria-Esther Vidal
چکیده

SemLAV allows to execute SPARQL queries against the Deep Web and Linked Open Data data sources. It implements the mediatorwrapper architecture based on view definitions over remote data sources. SPARQL queries are expressed using a mediator schema vocabulary, and SemLAV selects relevant data sources and rank them. The ranking strategy is designed to deliver results quickly based only on view definitions, i.e., no statistics, nor probing on sources are required. In this demonstration, we validate the effectiveness of SemLAV approach with real data sources from social networks and Linked Open Data. We show in different setups that materializing only a subset of ranked relevant views is enough to deliver significant part of expected results.

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تاریخ انتشار 2014