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| A Survey to Text Summarization: Popular Datasets and Methods |
| HOU Shengluan1,2, ZHANG Shuhan1,2, FEI Chaoqun1,2 |
1.Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;
2.University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract Text summarization has become an essential way of knowledge acquisition from mass text documents on the Internet. The existing surveys to text summarization are mostly focused on methods, without reviewing on the experimental datasets. This survey concentrates on evaluation datasets and summarizes the public and private datasets together with corresponding approaches. The public datasets are recorded for the data source, language and the way of access, and the private dataset are recorded with the scale, access and annotation methods. In addition, the formal definition of text summarization by each public dataset are provided. We analyze the experimental results of classical and latest text summarization methods on one specific dataset. We conclude with the present situation of existing datasets and methods, and some issues concerning them.
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Received: 28 June 2018
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2019, Vol. 33 
