E09-1079 shows the best accuracy for known word disambiguation . RF tagger shows the best accuracy
E03-2006 letter deletion , command mode or word disambiguation . Words are entered by pressing
A94-1007 governing the conjunctions make the word disambiguation more complicated , which results
I05-3030 Previous experiment had indicated word disambiguation could achieve better performance
D09-1090 was specifically designed for word disambiguation purposes in cross-language information
A00-1034 rules of spurious capitalized word disambiguation are designed to recognize the
J11-4005 each level of the hierarchy . A word disambiguation module might improve the learning
A83-1020 and Stone 's ( 1979 ) work on word disambiguation . The implication of which seems
C80-1034 semantic context . Similarly , some word disambiguations can be explained only by PIM
I05-3030 trigram , absolute smoothing and word disambiguation module and rough rules . There
C82-2014 place at + . he assembling level . Word disambiguation is treated in a non-deterministic
H94-1095 induce decision trees for cue word disambiguation based on lexical and part of
I05-3030 our system . In NE module and Word Disambiguation module , we introduce rough rule
E03-2006 of an ambiguous keyboard with word disambiguation for users of AAC devices are
C94-1050 interpretation . IIere we focus on word disambiguation as scene selection , based on
E14-1029 Constrained Clustering for Subjectivity Word Disambiguation </title> Cem Akkaya Janyce Abstract
J00-4009 lexical-semantic phenomena . Sanfilippo ( " Word disambiguation by lexical underspecification
A00-1034 , ( ii ) spurious capitalized word disambiguation , and ( iii ) spurious NE sequence
D11-1129 The evaluation is based on the word disambiguation task developed by Mitchell and
J02-3002 disambiguation task , the capitalized word disambiguation task , and the abbreviation identification
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