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Semantic Measures for the Comparison of Units of Language, Concepts or Instances from Text and Knowledge Base Analysis
Semantic measures are widely used today to estimate the strength of the
semantic relationship between elements of various types: units of language
(e.g., words, sentences, documents), concepts or even instances semantically
characterized (e.g., diseases, genes, geographical locations). Semantic
measures play an important role to compare such elements according to semantic
proxies: texts and knowledge representations, which support their meaning or
describe their nature. Semantic measures are therefore essential for designing
intelligent agents which will for example take advantage of semantic analysis
to mimic human ability to compare abstract or concrete objects. 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. Semantic measures generalize the well-known notions of semantic
similarity, semantic relatedness and semantic distance, which have been
extensively studied by various communities over the last decades (e.g.,
Cognitive Sciences, Linguistics, and Artificial Intelligence to mention a few).Comment: surve