A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations

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Proceedings titleProceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)
Conference22nd International Conference on Computational Linguistics (Coling 2008), August 18-22, 2008, Manchester, United Kingdom
Pages905912; # of pages: 8
AbstractRecognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated independently, using a wide variety of algorithms. These four semantic classes, however, are a tiny sample of the full range of semantic phenomena, and we cannot afford to create ad hoc algorithms for each semantic phenomenon; we need to seek a unified approach. We propose to subsume a broad range of phenomena under analogies. To limit the scope of this paper, we restrict our attention to the subsumption of synonyms, antonyms, and associations. We introduce a supervised corpus-based machine learning algorithm for classifying analogous word pairs, and we show that it can solve multiple-choice SAT analogy questions, TOEFL synonym questions, ESL synonym-antonym questions, and similar-associated-both questions from cognitive psychology.
Publication date
AffiliationNational Research Council Canada; NRC Institute for Information Technology
Peer reviewedNo
NRC number50398
NPARC number5764174
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Record identifierdbaa1cbc-effd-4e39-b430-7bf50a18b3d7
Record created2009-03-29
Record modified2016-05-09
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