Abstract
We deal with the issue of automatic discovery of similar words (synonyms and near-synonyms) from different kinds of sources: from large corpora of documents, from the Web, and from monolingual dictionaries. We present in detail three algorithms that extract similar words from a large corpus of documents and consider the specific case of the World Wide Web. We then describe a recent method of automatic synonym extraction in a monolingual dictionary. The method is based on an algorithm that computes similarity measures between vertices in graphs. We use the 1913 Webster’s Dictionary and apply the method on four synonym queries. The results obtained are analyzed and compared with those obtained by two other methods.
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Senellart, P.P., Blondel, V.D. (2004). Automatic Discovery of Similar Words. In: Berry, M.W. (eds) Survey of Text Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4305-0_2
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DOI: https://doi.org/10.1007/978-1-4757-4305-0_2
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