Automated sparql generation

Abstract

Observing the last decade, semantic data on web is increasing exponentially with time and it has become difficult for amateur users to retrieve information. An enhancement of the existing web is semantic web where semantics is attached with the information, allowing machine and users to work in cooperation. A RDF is a standard model for data interchange on web, developed to interlink large amount of Linked data for web semantic and to extract data efficiently in less amount of time. To retrieve data from RDF database, SPARQL is used as a standard query language. To use SPARQL it is necessary to have knowledge of all Uri’s which is unique for each resource in DBpedia, but to figure out the Uri’s for all the resources in not feasible and predicate is restricted to domain and range. In this work we propose an interface which maps the keyword into URI, a major step towards the automated SPARQL generation. Our system take keyword-SPARQL as input and produces SPARQL as output which can be executed on SPARQL endpoint. Studying the structure of DBpedia, we create an interface which provides Auto suggestion technique to users to resolve the general problems caused due to DBpedia structure and commonly occurring typing errors . Concept and property mapping functions are used to map instances to concept in DBpedia and WSD is used to resolve the predicate disambiguation. The advantage of this approach is that users, who are unaware of the Schema of DBpedia and complexity of SPARQL, can retrieve information.