Lexicons versus Corpora for Measures of Semantic Distance

Measures of semantic distance (or, inversely, semantic relatedness) have many applications in Computational Linguistics. There are three basic approaches to measuring semantic distance: lexicon-based algorithms, corpus-based algorithms, and hybrids. In an otherwise excellent paper on lexicon-based measures, Budanitsky and Hirst criticize corpus-based measures. I discuss their criticisms here.