Plaban Bhowmick

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We propose a new approach for extracting argument structure from natural language texts that contain an underlying argument. Our approach comprises of two phases: Score Assignment and Structure Prediction. The Score Assignment phase trains models to classify relations between argument units (Support, Attack or Neutral). To that end, different training(More)
In this paper, we propose a prototype system for automatic generation and insertion of assessment items in online video courses. The proposed system analyzes text transcript of a requested video lecture to suggest self-assessment items in runtime through automatic discourse segmentation and question generation. To deal with the problem of question(More)
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