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). Definitions, related contributions in cognitive sciences, practical applications, and the several approaches used for the definitions of semantic measures are presented. In addition, protocols and benchmarks for their evaluations, as well as, software solutions dedicated to them are introduced. The general presentation of the large diversity of existing semantic measures we propose is further completed by a detailed survey of a specific type of measures relying on knowledge representation analysis. This technical presentation mainly focuses on measures based on graph analyses. These measures are of particular interest for numerous communities and have recently gained a lot of attention in research and application, by taking advantage of several types of graph-based knowledge representations to compare words, concepts, or instances. We conclude this work by highlighting some of the challenges offered to the communities involved in the study of semantic measures