1) topic segmentation
文本段落划分
1.
This paper introduced the semi-markov Conditional Random Fields(semi-CRFs)model based method for Chinese Encyclopedia text topic segmentation.
介绍了基于半条件随机域(semi-Markov conditional random fields,简称semi-CRFs)模型的百科全书文本段落划分方法。
3) paragraph division
段落划分
1.
Music always has paragraph division.
音乐总是要有段落划分的,如果对曲式结构清楚了,对音乐的理解自然也就很容易更加深入了,在传统音乐中其重要标志便是和声终止式。
2.
In both Chinese and English argumentative essays there exist the following paragraph division modes: a paragraph develops around one topic sentence for global unity, two or more paragraphs center around one topic sentence, and one or more paragraphs develop around one implied topic with no topic sentence.
汉英议论文的段落划分模式都有三种,即一个自然段一个主题句,两个或多个自然段来论证一个主题句,以及自然段“主题句隐含”,但前者还有一个段落内含两个或多个主题意义的情况,后者则段落主题意义必须单一。
4) text segmentation
文本分段
5) text-fragment classification
文本片段分类
1.
The impact on text classification when text document is broken into fragments is analyzed; the most semantic marking rule (MSMR) and semantic inspiring rule (SIR) between paragraphs which are closely correlated to text semantics are defined; using these two rules, based on KNN (K-nearest-neighbor) algorithm, a context-sensitive text-fragment classification algorithm is designed and implemented.
该算法依据SIR判断文本片段分类的相互影响,降低了片段分类的错误率,当某一片断类隶属度大于某一阈值时,依据MSMR判定可知,同一文档的后续片断均属于同一类别,这样就不用计算所有片断的类隶属度。
6) Text Structure Division
文本层次划分
补充资料：段落
（文章、事情）根据内容划分成的部分：这篇文章～清楚，文字流畅ㄧ我们的工作到此告一～。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条