We Construct a system of Chinese automatic summarization based on conceptual vector space model.
开发了一个基于概念向量空间模型的中文自动文摘系统。
How to subdivide text into multi-paragraph units is an important issue in many NLP applications such as automatic summarization and QA system.
如何正确有效地确定文档的子主题边界对于自动文摘、问答系统等自然语言处理应用是非常重要的。
The experiment indicates that the system is better than present Chinese Web Automatic Summarization on content estimation and summary readability.
实验结果表明：本系统在对中文网页内容判断和摘要可读性，都优于目前一般网页的自动摘要设计。
The experiment indicates that the system is better than present Chinese Web Automatic Summarization on content estimation and summary readability.
实验结果表明：本系统在对中文网页内容判断和摘要可读性，都优于目前一般网页的自动摘要设计。
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