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The paper addresses the problem of extracting acronyms and their expansions from text. We propose a support vector machines (SVM) based approach to deal with the problem. First, all likely acronyms are identified using heuristic rules. Second, expansion candidates are generated from surrounding text of acronyms. Last, SVM model is employed to select the genuine expansions. Analysis shows that the...
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