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Learning Features that Predict Cue Usage
[article]
1997
arXiv
pre-print
Our goal is to identify the features that predict the occurrence and placement of discourse cues in tutorial explanations in order to aid in the automatic generation of explanations. Previous attempts to devise rules for text generation were based on intuition or small numbers of constructed examples. We apply a machine learning program, C4.5, to induce decision trees for cue occurrence and placement from a corpus of data coded for a variety of features previously thought to affect cue usage.
arXiv:cmp-lg/9710006v1
fatcat:27k7ltkdh5f55ijuvl2qkbb4v4