One of the most important steps in automatic summarization is to discover and extract the topic sentences.
自动文本摘要中一个关键的步骤是确定文章的主旨并将反映文章主旨的句子提取出来。
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。
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。
Text segmentation is very important in information retrieval, automatic summarization, discourse analysis, and many other fields.
文本分割在信息提取、文摘生成、语篇解析及其他多个领域有着极为重要的应用。
In order to obtain useful information fast and exactly, to raise the efficiency of getting information for the users, the automatic summarization becomes more and more important.
为了从这些丰富的信息中快速、准确地获取有用信息，提高用户获取信息的效率，文档的自动摘要处理变得越来越重要。
Others such as machine translation ( MT ), speech synthesis, automatic classification, automatic summarization, automatic proofreading etc. , require the use of word segmentation.
其他的比如机器翻译（MT）、语音合成、自动分类、自动摘要、自动校对等等，都需要用到分词。
With their high occurrence rates in argumentative Chinese texts, discourse markers play a significant role in the automatic processing of these kinds of Chinese texts, such as automatic summarization.
关联词语在一些汉语议论文章中占很大的比重，因而，对于此类汉语文章的分析，关联词可以起到非常重要的作用。
With their high occurrence rates in argumentative Chinese texts, discourse markers play a significant role in the automatic processing of these kinds of Chinese texts, such as automatic summarization.
关联词语在一些汉语议论文章中占很大的比重，因而，对于此类汉语文章的分析，关联词可以起到非常重要的作用。
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