The Semantic Measures Library: Assessing Semantic Similarity from Knowledge Representation Analysis

Semantic similarity and relatedness are cornerstones of numerous treatments in which lexical units (e.g., terms, documents), concepts or instances have to be compared from texts or knowledge representation analysis. These semantic measures are central for NLP, information retrieval, sentiment analysis and approximate reasoning, to mention a few. In response to the lack of efficient and generic software solutions dedicated to knowledge-based semantic measures, i.e. those which rely on the analysis of semantic graphs and ontologies, this paper presents the Semantic Measures Library (SML), an extensive and efficient Java library dedicated to the computation and analysis of these measures. The SML can be used with a large diversity of knowledge representations, e.g., WordNet, SKOS thesaurus, RDF(S) and OWL ontologies. We also present the SML-Toolkit, a command-line program which gives (non-programmers) access to several functionalities of the SML, e.g. to compute semantic similarities. Website: http://www.semantic-measures-library.org