Toward Inductive Lexicons: a Case Study
نویسندگان
چکیده
Machine learning techniques can be used to make lexicons adaptive. The main problems in adaptation are the addition of lexical material to an existing lexical database, and the recomputation of sublanguage-dependent lexical information when porting the lexicon to a new domain or application. Inductive lexicons combine available lexical information and corpus data to alleviate these tasks. In this paper, we introduce the general methodology for the construction of inductive lexicons, and discuss empirical results on a case study using the approach: prediction of the gender of nouns in Dutch.
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