Extracting semantic clusters from the alignment of definitions

Through tile alignment of definitions fronl two or more dilTerent sources, it is possible to retrieve pairs of words that can be used indistinguishably in the same sentence without changing tile meaning of the concept. As lexicographic work exploits common defining schemes, such as genus and dilTerentia, a concept is simihu'ly defined by different dictionaries. The dilTerence in words used between two lexicographic sources lets us extend lhe lexical knowledge base, so that clustering is available through merging two or more dictionaries into a single database and then using an approlwiate alignment techlaique. Since aligmnent starts from thc same entry of two dictionaries, clustering is l~lster than any other technique. Tile algorithm introduced here is analogybased, and starts from calculating the Levenshtein distance, which is a variation o1' the edit distance, and allows us to align the definitions. As a measure of similarity, the concept el' longest collocation couple is introduced, which is the basis of clustering similar words. The process iterates, replacing similar pairs of words in tile definitions until no new clusters are found.