采用最大熵模型实现中文组块分析的任务。
This paper proposes to use Maximum Entropy (ME) model to conduct Chinese chunk parsing.
组块分析是一种大大降低句法分析难度的有效手段。
Chunk parsing is an effective method to decrease the difficulty of language parsing.
汉语组块分析是中文信息处理领域中一项重要的子任务。
Chinese chunking plays an important role in natural language processing.
本文首先指出当前语法分析的困难，而组块分析是一条解决问题的途径。
At first, we point out the difficulties of syntactic parsing and think that chunk parsing is one way to solve this problem.
实验结果说明最大熵模型应用于汉语问句语义组块分析具有较好的效果。
The experiment results show that the maximum entropy model has a very good effect on semantic chunk parsing to Chinese question sentence.
本文中对组块的计算，不仅包括组块分析，还涉及到对组块相似度计算的研究。
In this paper, the computation of chunks not only includes chunk parsing, but also refers to the computation of similarity between chunks.
接着本文运用组块分析的思想，提出并实现了一个基于语义的汉语句法分析系统。
Then according to the idea of chunk parsing, the Chinese parsing system based on semantic analysis is designed and is implemented.
为了降低完全句法分析的难度，研究人员提出了“分而治之”的策略，进行浅层分析也就是组块分析。
In order to reduce the difficulty of complete syntactic parsing, "divided-and-conquer" is proposed and shallow parsing is processed.
文本组块分析作为句法分析的预处理阶段，通过将文本划分成一组互不重叠的片断，来达到降低句法分析的难度。
The text chunking, as a preprocessing step for parsing, is to divide text into syntactically related non-overlapping groups of words (chunks), reducing the complexity of the full parsing.
文本组块分析作为句法分析的预处理阶段，通过将文本划分成一组互不重叠的片断，来达到降低句法分析的难度。
The text chunking, as a preprocessing step for parsing, is to divide text into syntactically related non-overlapping groups of words (chunks), reducing the complexity of the ful.
句法分析一直是自然语言处理的一个基础性的研究课题，近年来部分分析，也叫浅层分析、组块分析，成为自然语言处理的热点。
Syntax analysis is always a basic task in the natural language processing, part analysis, also called shallow parse or chunk identification, becomes a hotspot in the natural language processing.
在中文问句的结构特点基础上，结合机器学习及组块分析理论，对问句进行组块分析，实现了基于神经网络的问句组块识别算法，并应用于银行领域自动问答系统中。
Based on the structure feature of the question, machine learning and chunk parsing theory, an approach for question chunk parsing using neural networks is implemented.
介绍了组块设计的实验设计方式，在此基础上对功能磁共振成像实验数据进行处理，详细介绍了实验数据的预处理过程和统计分析的原理和方法。
The block design is introduced, and based on these methods, the fMRI data processing is detailed analyzed, the data pre-processing and statistical methods are introduced.
介绍了组块设计的实验设计方式，在此基础上对功能磁共振成像实验数据进行处理，详细介绍了实验数据的预处理过程和统计分析的原理和方法。
The block design is introduced, and based on these methods, the fMRI data processing is detailed analyzed, the data pre-processing and statistical methods are introduced.
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