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Semantic-based information retrieval techniques understand the meanings of the concepts that users specify in their queries. The main drawback of the existing semantic-based information retrieval techniques is that none of them considers the context of the concept(s). We propose a semantic information retrieval framework to improve the precision of search results. In this paper, thematic similarity approach is employed for information retrieval in order to capture the context of particular concept(s). We store metadata information of source(s) in the form of RDF triples. We search userpsilas queries in the existing metadata by matching RDF triples instead of keywords. The results of the experiments performed on our framework showed improvements in precision and recall compared to the existing semantic-based information retrieval techniques.