D08-1047 for generating candidates for string transformation . Unlike conventional spelling-correction
D08-1047 also affects the accuracy of the string transformation . Previous studies of spelling
D13-1008 memorizing phrases are captured with string transformations . For in - stance , from phrase
E97-1057 computational problem of learning string transformations from an aligned corpus . We show
D08-1047 allows only one region of change in string transformation . A natural extension of this
D08-1047 essential and important step for string transformation is to generate candidates to
D08-1047 However , this study addresses string transformation in its narrow sense , in which
D08-1047 generator because the processes of string transformations are intractable in their discriminative
D08-1047 variations . 3.3 Experiment 2 : String transformation The second experiment examined
D08-1047 spelling variations . 1 Introduction String transformation maps a source string s into its
C04-1117 cognate stems applying simple string transformation rules . We then used the local
D09-1154 draws on some previous work on string transformation , including spelling normalization
D08-1047 ∗ . In the broad sense , string transformation can include labeling tasks such
D08-1047 framework . 4 Related work The task of string transformation has a long history in natural
E97-1057 Satta John C Henderson Abstract String transformation systems have been introduced
D08-1047 be inappropriate for expressing string transformation because it always removes the
E97-1057 assumptions of the approach . A string transformation is a rewriting rule denoted as
D08-1047 algorithm because the processes of string transformation are tractable in the model .
E97-1057 for the experiments . <title> String Transformation Learning </title> Giorgio Satta
J79-1008 location of clause boundaries , string transformations are necessarily relatively local
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