P06-1045 WordNet , thus more accurate the synonym acquisition result is . The value of CC is
P06-1045 the target vocabulary set for synonym acquisition . Proper nouns are omitted from
P06-1045 critical impact on the performance of synonym acquisition . This is an independent problem
P06-1045 2005 ) have been proposed for synonym acquisition . Most of the acquisition methods
P06-1045 methods we employed for automatic synonym acquisition . The evaluation is to measure
N13-1075 might use methods for automatic synonym acquisition like described in ( Grefenstette
P06-1045 have been proposed for automatic synonym acquisition , as synonyms are one of the
P06-1045 following Section 3 explains the synonym acquisition method . In Section 4 the evaluation
P08-3001 performances are compared in terms of synonym acquisition precision and recall , and the
W10-3304 target word . The performance on synonym acquisition when using translational contexts
P06-1045 utilizing modification relationship in synonym acquisition is n't the type of modification
P06-1045 suppose is most commonly used for synonym acquisition as the context of words . The
P06-1045 Because nouns are the main target of synonym acquisition , here we limit the target of
W10-3304 incomplete . In previous work on synonym acquisition for the general domain , Van
P06-1045 for word featuring in terms of synonym acquisition . For example , Hindle ( 1990
P06-1045 Probabilistic LSI ( Hofmann , 1999 ) and synonym acquisition method , almost no attention
P08-3001 this purpose , we re-formalized synonym acquisition as a classification problem ,
P06-1045 representation that we require for synonym acquisition , that is , the co-occurrence
P06-1045 Contextual Information for Automatic Synonym Acquisition </title> Masato Hagiwara Yasuhiro
P08-3001 technique . Firstly , we re-formalize synonym acquisition as a classification problem :
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