Contributions to Books:
A. M. El-Ebshihy:
"Semi-automatic Labelling of Scientific Articles using Deep Learning to Enlarge Benchmark Data for Scientific Summarization";
in: "SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval",
ACM Digital Library,
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.
Created from the Publication Database of the Vienna University of Technology.