Bridging the gap for retrieving DBpedia data

Citations Over TimeTop 18% of 2015 papers

Abstract

DBpedia is nowadays considered one of the main projects in the World Wide Web that extracts and enriches Wikipedia data in a structured form. Also, it is considered the central hub for the Linked Open Data. Querying DBpedia using big data approaches such as Hive-QL is regarded as one of the new techniques to solve the shortcomings of SPARQL; the main query language of DBpedia and the Semantic Web. Nevertheless, despite the speed of Hive-QL compared to SPARQL, it has a stability problem. Our paper presents a new architecture and implementation for querying DBpedia using Shark query language in addition to Hive-QL. As a result of this work, An obvious decrease in execution time, as well as, an increase in the degree of stability have been attained.

Related Papers

• → A SPARQL Extension for Generating RDF from Heterogeneous Formats(2017)135 cited
• → Sparqling kleene(2013)41 cited
• → Efficiently Finding Paths Between Classes to Build a SPARQL Query for Life-Science Databases(2016)6 cited
• → A General Framework for Querying Possibilistic RDF Data(2018)2 cited
• → RDF/SPARQL Design Pattern for Contextual Metadata(2007)9 cited