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Regardless of the knowledge structure lack about Resource Description Framework (RDF) data, difficulties, principally, occur in specifying and answering queries. Approximate querying is the solution to find relevant information by getting a set of sub structures (e.g. sub graphs) matching the query. Approaches based on the structure and others based on semantic, marginalized the common meaning between concepts in its computing. In this paper in order to improve the approximation by introducing the meaning similarity between components in the query and RDF components is proposed, getting better need satisfaction. The meaning similarity measure can be calculated using WordNet and used in all steps of the query answering process. In addition, other important properties in the approximation level calculation between query paths and RDF paths are considered; besides indexing and optimizations strategies are performed. Answers are a set of sub graphs ranked in decreasing order on its matching degree. Experiments are conducted within real RDF dataset.