Jacky Montmain

TL;DR: A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.

TL;DR: This paper presents a unifying framework that aims to improve the understanding of semantic measures, to highlight their equivalences and to propose bridges between their theoretical bases, and unify a large number of state-of-the-art semantic similarity measures through common expressions.

TL;DR: The semantic measures library and toolkit are robust open-source and easy to use software solutions dedicated to semantic measures that can be used for large-scale computations and analyses of semantic similarities between terms/concepts defined in terminologies and ontologies.

TL;DR: Semantic measures as discussed by the authors assess the similarity or relatedness of semantic entities by taking into account their semantics, i.e. their meaning; intuitively, the words tea and coffee, which both refer to stimulating beverages, will be estimated to be more semantically similar than the words toffee (confection) and coffee despite that the last pair has a higher syntactic similarity.

TL;DR: This paper proposes a comprehensive survey of the broad notion of semantic measure for the comparison of units of language, concepts or instances based on semantic proxy analyses, which generalize the well-known notions of semantic similarity, semantic relatedness and semantic distance.