Automatic text summarization is widely regarded as the highly difficult
problem, partially because of the lack of large text summarization data set.
Due to the great challenge of constructing the large scale summaries for full
text, in this paper, we introduce a large corpus of Chinese short text
summarization dataset constructed from the Chinese microblogging website Sina
Weibo, which is released to the public
{this http URL}. This corpus consists of over
2 million real Chinese short texts with short summaries given by the author of
each text. We also manually tagged the relevance of 10,666 short summaries with
their corresponding short texts. Based on the corpus, we introduce recurrent
neural network for the summary generation and achieve promising results, which
not only shows the usefulness of the proposed corpus for short text
summarization research, but also provides a baseline for further research on
this topic.

本文介绍了一个由新浪微博构建的大型中文短文本摘要数据集，包含超过 200 万条中文短文本和对应的短摘要，并通过该数据集引入了基于递归神经网络的摘要生成方法，取得了良好的效果，该方法不仅显示了所提出数据集在短文本摘要研究中的有用性，也为后续研究提供了基线。