.png){kind=icon}
返回
Citance-based retrieval and summarization using IR and machine learning
.png){kind=icon}
PRE
AI
DOI：10.1007/s11192-018-2785-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We consider the three interesting problems posed by the CL-SciSumm series of shared tasks. Given a reference document D and a set of citances for D: (1) find the span of reference text that corresponds to each citance , (2) identify the facet corresponding to each span of reference text from a predefined list of five facets, and (3) construct a summary of at most 250 words for D based on the reference spans. The shared task provided annotated training and test sets for these problems. This paper describes our efforts and the results achieved for each problem, and also a discussion of some interesting parameters of the datasets, which may spur further improvements and innovations.
Keyword:
Citance-based summarization
Structural correspondence learning
Positional language model
Textual entailment
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
8.1K
被引数:
2.2W
机构
引用论文
The Effect of Electron Irradiation on the Structure of Sodium Aluminum-Iron Phosphate Glasses电子辐照对磷酸铝铁钠玻璃结构的影响.png)
MRS Advances
MRS AdvancesIF0
PREAI
分享收藏
查看更多内容