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2015•Unpublished venueRequires access

Bridging the gap for retrieving DBpedia data

Ahmed S. Ismail, Haytham Al-Feel, Hoda M. O. Mokhtar

Open publisher page 3 citations

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.

About this research paper

What this paper is about

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.

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Available 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.

Key concepts: SPARQL, Computer science, Linked data, Bridging (networking), Information retrieval, Semantic Web, Named graph, RDF

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