[1804.04589] A Survey on Neural Network-Based Summarization Methods
Future research directions such as adding the reinforcement learning algorithms and text simplification methods to the current neural-based models are provided to the researchers.
Abstract: Automatic text summarization, the automated process of shortening a text
while reserving the main ideas of the document(s), is a critical research area
in natural language processing. The aim of this literature review is to survey
the recent work on neural-based models in automatic text summarization. We
examine in detail ten state-of-the-art neural-based summarizers: five
abstractive models and five extractive models. In addition, we discuss the
related techniques that can be applied to the summarization tasks and present
promising paths for future research in neural-based summarization.