Towards Supervised Extractive Text Summarization via RNN-based Sequence Classification

This article briefly explains our submitted approach to the DocEng19 competition on extractive summarization. We implemented a recurrent neural network based model that learns to classify whether an articles sentence belongs to the corresponding extractive summary or not. We bypass the lack of large annotated news corpora for extractive summarization by generating extractive summaries from abstractive ones, which are available from the CNN corpus.