问答系统是信息检索的高级形式，也是该领域的研究重点和热点。
Question Answering system is an advanced form of information retrieval, as well as a hot topic of this field.
自动问答系统一般包括三个主要组成部分：问题分析、信息检索和答案抽取。
In general, a Question Answering system is made up of three parts: Question Analysis, Information Retrieval and Answer Extraction.
自动问答系统是自然语言理解研究领域中的热门方向，它综合运用了多种自然语言处理技术。
The automatic question and answering system (QA) is a hot research field in natural language understanding, which includes many kinds of NLP technologies.
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。
How to subdivide text into multi-paragraph units is an important issue in many NLP applications such as automatic summarization and QA system.
问题分类是问答系统处理的基础。
Question classification is the basis of a question-answering system.
介绍了有关中文问答系统的一些研究。
Research on Chinese question answering system is presented in this paper.
其中一个很重要的方向就是问答系统。
One of the most important directions is Question Answering system.
其中一个很重要的方向就是问答系统。
One of the most important directions is Question Answering (QA) system.
答案确认是问答系统中的关键环节之一。
Answer validation is one of the most important stages in question answering system.
该方法的实现将有效提高问答系统的实用性。
The method will efficiently improve the practicability of QA system.
问答系统中问句类型的判定与实体的识别紧密相关。
The judgement of question type is very related to entity recognition in QAS.
本文设计并实现了一个基于常问问题库的中文问答系统。
In this paper, we describe the design and implementation of a question answer system based on FAQ (Frequently-asked question).
所以，大部分问答系统只采用词、词性、句法关系等信息。
That is why most systems only use words, part of speech and syntactic relations in question answering system.
问答系统由问题理解、信息检索、答案抽取三个部分组成。
Question answering system is composed of three parts which is question analysis, information retrieval and answer extraction.
而问题理解是问答系统的第一部分也是非常关键的一部分。
Question understanding is the first and the very important part of QA system.
本文主要研究了问答系统的问题理解与答案抽取两个部分。
This paper mainly focuses on question analysis and answer extraction. Question analysis includes question classification, keyword extraction and keyword expansion.
问答系统是信息检索的高级形式，也是该领域的研究重点和热点。
Question Answering System (QAS) is both high-level form of information retrieval and research emphasis and hotspot in this field.
问答系统中包括三个主要的部分：问题理解，信息检索和答案抽取。
QA system contains three main procedures: question understanding, information retrieve and answer extraction.
实验结果表明，本算法可以有效的解决中文问答系统的模式推理问题。
The experiment results indicate that this algorithm is effective, and can solve the problem of pattern reasoning in Chinese question answering system.
同时它能够对问答系统、信息抽取和机器翻译等应用产生巨大帮助。
In addition, it can give great support to many NLP applications, such as information extraction, question and answering, machine translation and so on.
本文旨在探索如何使用领域本体的语义信息来提升自动问答系统的性能。
This thesis aims to research how to use the semantic information of domain ontology to improve the performance of Question Answering System.
然后将语义角色信息用于问答系统的答案抽取中，提高了问答系统的精度。
Then semantic roles of sentences are used in answer extraction of the question answering system, and it improves the system's accuracy.
此方法易于结合到自动问答系统以及一些游戏领域的系统中，应用前景明朗。
This method can be combined to the automatic question answering system and some game domain's systems easily, and the application prospect is bright.
提出了一种基于本体的自动问答系统模型，对领域知识本体的构建进行了研究。
A model of question answering system is put forward based on ontology. The building of the domain is introduced.
问答系统是集自然语言处理技术和信息检索技术于一身的新一代智能搜索引擎。
Question answering is the next generation of search engine which is related to natural language processing, information retrieval and etc.
与传统的搜索引擎相比，自动问答系统在理论上能够更好地满足用户的检索需求。
Compared to traditional search engines, Automatic Question Answering System is theoretically better to meet the needs of the user's search.
自动问答系统是集自然语言处理技术和信息检索技术于一身的新一代智能搜索引擎。
Question Answering (QA) is the next generation of search engine which is related to natural language processing, information retrieval and etc.
搜索引擎，要求输入的是一些关键字的组合，而自动问答系统允许用户输入一个问句；
The inputs of search engines are combinations of keywords, while QA systems enable users to input a question in natural languages.
搜索引擎，要求输入的是一些关键字的组合，而自动问答系统允许用户输入一个问句；
The inputs of search engines are combinations of keywords, while QA systems enable users to input a question in natural languages.
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