W97-0323 presented improvements to the exemplar-based learning approach for WSD . By using a
W97-0323 Algorithms 2.1 PEBLS The heart of exemplar-based learning is a measure of the similarity
P96-1006 disambiguation ( WSD ) using an exemplar-based learning algorithm . This approach integrates
W97-0323 report recent improvements to the exemplar-based learning approach for WSD that have achieved
W97-0323 1996 ) . It demonstrates that an exemplar-based learning approach is suitable for the
W00-1322 Exemplar-based Classifier ( EB ) In Exemplar-based learning ( Aha et al. , 1991 ) no generalization
W12-5206 shared task . As in other types of exemplar-based learning techniques , DOP models require
W97-0323 report recent improvements to the exemplar-based learning approach for word sense disambiguation
J01-3001 They describe this approach as " exemplar-based learning " although it is also known as
J01-3001 PEBLS , a publically available exemplar-based learning algorithm . A set of features
P96-1006 is used . In contrast , we used exemplar-based learning , where the contributions of
J01-3001 Memory-based learning is another name for exemplar-based learning , as employed by Ng and Lee (
W97-0323 disambiguation accuracy . The exemplar-based learning algorithm PEBLS contains a number
W97-0323 example . LEXAS then uses the exemplar-based learning algorithm PEBLS ( Cost and Salzberg
W97-0323 decision lists ( Yarowsky , 1994 ) , exemplar-based learning algorithms ( Cardie , 1993 ;
W00-0706 learning ( Bruce and Wiebe , 1999 ) , Exemplar-based learning ( Ng , 1997 ) , Boosting ( Escudero
W97-0108 LEXAS algorithm which uses an exemplar-based learning framework similar to the case-based
W00-0706 ( WSD ) , namely Naive Bayes , Exemplar-based learning , SNoW , Decision Lists , and
W97-0323 . One potential drawback of an exemplar-based learning approach is the testing time
W00-1322 learning ( Bruce and Wiebe , 1999 ) , Exemplar-Based learning ( Ng , 1997a ; Fujii et al. ,
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