We provide a literature review about Automatic Text Summarization (ATS)
systems. We consider a citation-based approach. We start with some popular and
well-known papers that we have in hand about each topic we want to cover and we
have tracked the "backward citations" (papers that are cited by the set of
papers we knew beforehand) and the "forward citations" (newer papers that cite
the set of papers we knew beforehand). In order to organize the different
methods, we present the diverse approaches to ATS guided by the mechanisms they
use to generate a summary. Besides presenting the methods, we also present an
extensive review of the datasets available for summarization tasks and the
methods used to evaluate the quality of the summaries. Finally, we present an
empirical exploration of these methods using the CNN Corpus dataset that
provides golden summaries for extractive and abstractive methods.

本文综述了自动文本摘要的研究现状及其评估方法，使用引用文献的方法考察各种摘要生成机制，同时对可用于摘要任务的数据集进行了广泛的回顾，并在 CNN 语料库数据集上进行了抽取和生成方法的实证研究。