liuhuanyong/TextGrapher
liuhuanyong/TextGrapher has 1,475 GitHub stars and 357 forks. GitHot measured 0 stars in 24 hours and +2 in 7 days. Last checked 2026-11-10 04:08 UTC. Last push 2021-10-20.
Text Content Grapher based on keyinfo extraction by NLP method。输入一篇文档,将文档进行关键信息提取,进行结构化,并最终组织成图谱组织形式,形成对文章语义信息的图谱化展示。
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README.md
OriginalTextGrapher
Text Content Grapher based on keyinfo extraction by NLP method。输入一篇文档,将文档进行关键信息提取,进行结构化,并最终组织成图谱组织形式,形成对文章语义信息的图谱化展示。
项目介绍
如何用图谱和结构化的方式,即以简洁的方式对输入的文本内容进行最佳的语义表示是个难题。 本项目将对这一问题进行尝试,采用的方法为:输入一篇文档,将文档进行关键信息提取,并进行结构化,并最终组织成图谱组织形式,形成对文章语义信息的图谱化展示。
使用方式
from text_grapher import *
content = '你要分析的文本'
handler = CrimeMining()
handler.main(content)
结果保存在graph.html文件当中。
事件举例
1) 中兴事件

魏则西事件

雷洋事件

同学杀人事件

总结
1)如何用图谱和结构化的方式,即以简洁的方式对输入的文本内容进行最佳的语义表示是个难题。
2)本项目采用了高频词,关键词,命名实体识别,主谓宾短语识别等抽取方式,并尝试将三类信息进行图谱组织表示,这种表示方式是一种尝试。
3)命名实体识别以及关键信息抽取受限于NLP的性能,在算法和方式上还存在多处不足。
Question?
send mail to [email protected]
If any question about the project or me ,see https://liuhuanyong.github.io/
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