Predicting proficiency levels in learner writings by transferring a linguistic complexity model from expert-written coursebooks

COLING 2016 Ildik{\'o} Pil{\'a}nElena VolodinaTorsten Zesch

The lack of a sufficient amount of data tailored for a task is a well-recognized problem for many statistical NLP methods. In this paper, we explore whether data sparsity can be successfully tackled when classifying language proficiency levels in the domain of learner-written output texts... (read more)

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