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.
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.
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.
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.
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.
本文“语句自动分类”的思想是在IT领域自动问答系统的研究中产生并形成的。
The idea of automatic sentence classification comes of the study on automatic QA system about IT domain.
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.
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.
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 mang kinds of NLP technologies.
本文的研究成果可以很好地应用于自动内容抽取、自动问答系统、话题追踪结果及自动文摘系统中。
This paper' s research can be used very well in automatic content extraction, auto QS system, topic detection and tracking, automatic summary system and so on.
为了改善真实网络数据集上自动问答系统的性能，定义出新的问题类别集合和通用的答案重新排序模型。
To improve question answering (QA) performance based on real-world web data sets, a new set of question classes and a general answer re-ranking model are defined.
自动问答系统是自然语言处理研究中的一个热门的研究方向，主要集问题分析、信息检索、答案抽取等于一体。
Question answer System is a subject of great topic study orientation in studying natural language processing, mainly including question analysis, information retrieval and answer collection.
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.
提出基于FAQ自动问答技术来构建网校自动答疑系统，完成系统设计与开发。
This paper put forward a method of automatic question-answering system based on FAQ technology for net-schools and described the design and implementation of the system.
提出基于FAQ自动问答技术来构建网校自动答疑系统，完成系统设计与开发。
This paper put forward a method of automatic question-answering system based on FAQ technology for net-schools and described the design and implementation of the system.
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