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Most Web of Data applications focus mainly on using SPARQL for issuing queries. This leads to theWeb of Data being difficult to access for non-experts. Another problem that will intensify this challenge is when applying the algorithms on large-scale and decentralized knowledge bases. In the current thesis, firstly we focus on the methods for transforming keyword-based queries into SPARQL automatically. Secondly, we will work on improving those methods in order to apply them on (a large subset of) the Linked DataWeb. In an early phase, a heuristic method was proposed for generating SPARQL queries out of arbitrary number of keywords. Its preliminary evaluation showed promising results. So, we are working on the possible improvements for applying that on the large-scale knowledge bases.