期刊论文

Recognizing and Analyzing Cited Spans in Literature

中文

数据分析与知识发现

2096-3467

2017

1

11

37-45

10.11925/infotech.2096-3467.2017.0606

本校为其他机构

【目的】对科技文献领域的被引片段概念的特征进行分析,并比较不同识别方法效果的差异。【方法】以CL-Sci Summ 2016比赛被引片段标注数据为例,探索被引片段长度、位置与重要性特征,并分析与其对应引文上下文在长度和位置上的相关性。之后以基于词袋模型、主题模型、Word Net语义词典的相似性算法为例,比较这些方法在被引片段识别中的效果差异。【结果】研究结果发现:被标注的被引片段有96%少于三句,且更多地出现在文章前部和章节内的前部分,被引片段的Text Rank权重均值显著高于其他片段;被引片段与引文上下文在长度上显著相关,但在出现位置上相关性不明显;无论从MMR?还是句子与词汇层面的匹配...

[Objective] This paper analyzes features of the cited document spans, and compares the effectiveness of several recognization techniques. [Methods] Firstly, we analyzed the annotated data of cited spans from CL-Sci Summ 2016 for their length and position features as well as correlations with citation contexts. Then, we compared the effectiveness of bag-of-words, topic model, semantic dictionary（Word Net） methods by their performance of recognizing cited spans. [Results] We found that 96% of the annotated cited spans were less than three sente...