Keyword-Based SPARQL Query Generation System to Improve Semantic Tractability on LOD Cloud

Abstract

As the number of RDF triples on the Linking Open Data (LOD) Cloud has been exponentially increased, the difficulties of information query have been increased. To query information on the LOD Cloud, the users have to have some capabilities for developing SPARQL and/or RDQL query statements and exact knowledge for web resources with RDF such as URI, DB title, and name of things. However, it is almost impossible to require the capabilities and/or knowledge to the users who are familiar with keywords search. So, we propose fully automated keyword-based SPARQL query generation system. In our system, the users can query information on the LOD Cloud without having capabilities about structured query language and having prior knowledge of web resources with RDF. The users should type a set of keywords into our system. To do so, we developed a propertybased path finding algorithm and an automated SPARQL query generation that can be used to provide query recommendations for the users. In the experimental section, we illustrate an example to validate the effectiveness of our system, and perform a simulation to show the superiority of the algorithms. The experiment results are not bad for a first attempt. If we improve the algorithms, we can expect a better result.