一种基于中心点的新型句子分类方法,用于提取COVID-19新闻报道的摘要总结
Sumanta Banerjee1, Shyamapada Mukherjee1, Sivaji Bandyopadhyay1
1Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam 788010 India.
概括
这项研究为COVID-19新闻引入了一种新的查询集中总结 (QFS) 方法,实现0.60-0.63.3之间的平均F1分数. 该方法有效地总结了基于读者特定子话题的新闻,使用矢量空间模型和监督句子分类.
科学领域:
- 自然语言处理自然语言处理.
- 信息检索 信息检索
- 计算语言学 计算语言学
背景情况:
- COVID-19新闻报道涵盖了各种各样的子话题,包括感染,经济影响和就业.
- 自动新闻总结需要能够适应读者特定兴趣的方法.
- 现有的总结技术可能无法充分解决新闻文章中细微的子话题.
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