Computing the semantic similarity between terms relies on existence and usage of semantic resources. However, these resources, often composed of equivalent units, or synonyms, must be first analyzed and weighted in order to define within them the reliability zones where the semantic cohesiveness is stronger. We propose an original method for acquisition of elementary synonyms based on exploitation of structured terminologies, analysis of syntactic structure of complex (multi-unit) terms and

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... r compositionality. The acquired synonyms are then profiled thanks to endogenous lexical and linguistic indicators (other types of relations, lexical inclusions, productivity), which are automatically inferred within the same terminologies. Additionally, synonymy relations are observed within graph, and its structure is analyzed. Particularly, we explore the usefulness of the graph theory notions such as connected component, clique, density, bridge, articulation vertex, and centrality of vertices.