Semi-automatic Labelling of Scientific Articles using Deep Learning to Enlarge Benchmark Data for Scientific Summarization

Scientific article summarization is a challenging task not least due to the lack of large annotated corpora. In this research proposal, we present an approach to construct a large annotated corpus for scientific articles using semi-supervised/automatic annotation approaches. We intend to apply deep learning methods to increase a small seed of annotated corpus. Then, we will measure the quality of the annotated corpus on down stream informative summaries using various evaluation techniques.