长期以来，诸多的现代汉语教材在对多重短语的层次分析上，对一些具体问题的处理上，都有自己的一套方法，且都有不尽人意之处。
For a long time, analysis of levels of multiple phrases in most of the modern Chinese textbooks varied in their methods but not so perfectly.
在自然语言处理中，短语在汉语分析中占有举足轻重的地位。
In natural language processing, the phrase holds the pivotal status in Chinese analysis.
简单分析了语法上界定汉语短语的困扰，提出一种利用语义搭配关系界定汉语短语的方法。
After simply analyzing of puzzles in locating Chinese phrases boundaries with syntax, a method utilizing semantic collocations to parse phrases is presented.
针对框架语义分析的目的，在分析真实语料的基础上，提出了适合于框架语义分析的汉语名词短语的定义。
Focusing on the aim of frame semantic analysis, through analyzing practical corpus, this paper presents the definition of noun phrase for the frame semantic analysis.
量词和含量词短语的分析排歧是汉语文本自动分析中的难点之一。
One of the most difficult points in Chinese text automatic analysis is to analyse and disambiguate classifier and phrase containing classifier.
对汉语短语句法规则进行符号化形式化的分析，给出了句法模型，定义了一整套汉语的句法规则体系及相应的语义处理方案。
In order to build a complete analysis system of Chinese syntactic rules, we have defined the sets of words, attribute, pinyin, relations, terminals and non terminals for the syntactic analysis.
该文分析了已有短语抽取技术，并结合汉语特点，提出了基于概率统计技术和规则方法相结合的概念抽取方法。
The paper gives the method based on probabilistic techniques and rules for new word discovery via analyzing the current techniques of phrase extraction and combining the specialties of Chinese.
为此，论文分析了汉语文本的语法结构与韵律结构之间的关系，重点研究了韵律词和韵律短语的预测。
The thesis studied the relationship between prosodic structure and syntax structure, and focused on the methods of predicting the boundary of prosodic word and prosodic phrase.
为提高计算机对汉语信息的处理能力，更好地进行浅层句法分析，提出一种基于最大熵的汉语短语结构识别方法。
To improve the computer's processing capacity on Chinese information, and do better shallow parsing, this paper presents a recognition method of Chinese phrase structure based on Maximum Entropy(ME).
为提高计算机对汉语信息的处理能力，更好地进行浅层句法分析，提出一种基于最大熵的汉语短语结构识别方法。
To improve the computer's processing capacity on Chinese information, and do better shallow parsing, this paper presents a recognition method of Chinese phrase structure based on Maximum Entropy(ME).
应用推荐