This paper focuses on some kernel techniques on Intelligent Question answering system.
本文围绕智能答疑系统一些关键技术进行了研究分析。
Question Answering system is an advanced form of information retrieval, as well as a hot topic of this field.
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。
That is why most systems only use words, part of speech and syntactic relations in question answering system.
所以，大部分问答系统只采用词、词性、句法关系等信息。
A model of question answering system is put forward based on ontology. The building of the domain is introduced.
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。
Question answering system is composed of three parts which is question analysis, information retrieval and answer extraction.
问答系统由问题理解、信息检索、答案抽取三个部分组成。
A segmentation algorithm without dictionary based on network-oriented natural language question answering system is proposed.
提出了一种面向网络答疑系统的无词典分词方法。
Question understanding is an important part of Question Answering system, especially to the Cooperate Question Answering system.
问题理解是问答系统中的重要组成部分，尤其对于协作式问答，用户对所提出的问题进行了详细的说明、描述。
Question Answering System (QAS) is both high-level form of information retrieval and research emphasis and hotspot in this field.
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。
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。
Answer ranking is one of the key technologies in the question answering system, and the confidence score is used to rank the answers.
答案排序是问题回答中的关键技术之一，它通过计算答案的置信度来对候选答案进行排序。
Then semantic roles of sentences are used in answer extraction of the question answering system, and it improves the system's accuracy.
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 we employ Bayesian classifier to classify these questions. Answer extraction is the most crucial part for question answering system.
本文采用贝叶斯分类器，提取问句主干以及包含疑问词的分支作为特征进行问题分类。
Compared to traditional search engines, Automatic Question Answering System is theoretically better to meet the needs of the user's search.
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。
This thesis aims to research how to use the semantic information of domain ontology to improve the performance of Question Answering System.
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。
Question answering system can give users precise answer to the question presented in natural language by using natural language processing technique.
问答系统通过采用自然语言处理技术，用简洁准确的语言回答用户用自然语言提出的问题。
This method can be combined to the automatic question answering system and some game domain's systems easily, and the application prospect is bright.
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。
The experiment results indicate that this algorithm is effective, and can solve the problem of pattern reasoning in Chinese question answering system.
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。
This paper introduces several key technologies of QA, then analyses methods and characteristics of sentence retrieval in Chinese question answering system.
本文首先简单介绍了问答系统中的几种关键技术，然后对问答系统中信息检索模块句子检索的方法和特点进行了分析。
The innovative solution has been already applied to the natural language intelligent network Question Answering system. The application achieved well results.
目前，该方法已经用于基于自然语言的智能网络答疑系统中，并取得了较好的效果。
Question classification is an important component of the question answering system, its result directly influences the performance of the question answering system.
问题分类是问答系统中重要的组成部分，问题分类结果的好坏直接影响问答系统的性能。
This theory combined the excellence of current Question Answering System and is hoped to fulfill the mechanism of retrieval, understanding and reasoning based on pure text knowledge.
该理论综合了现有问答系统的优点，有望基于纯粹的文本知识，实现检索、理解、推理一体化的机制。
Question analysis is the primary task of Question answering System. The result of Question analysis has a great effect on following processing work, even on finding the correct answer.
问题理解是问答系统的首要的分析工作，分析的结果对后面的处理，以至找到问题的正确答案都有很大的影响。
Finally, this paper gives the implementation of acquiring answers to method type questions as well as the application in natural language intelligent network question Answering system.
最后，给出方法类答案获取的实现及其在自然语言智能网络答疑系统中的应用。
This paper introduces how to use the concept of Role Inverse Algorithm in order to build syntactic parser in the various information resources based multi-lingual question answering system.
该文介绍了如何将角色反演算法的思想用在多信息源多语种问答系统中来构建句法分析器。
They are an exploratory way of learning the system and answering the question, 'Is there a problem here?'
测试是了解系统和解答问题的探索之旅：“这里有问题吗？”
No question migrating birds are answering a command of nature, but now the bad news: There is growing evidence that the wiring is off; the system is breaking down.
毫无疑问，迁徙的候鸟听从着大自然的召唤，但现在的坏消息是，有越来越多的证据表明，“硬线”正在断开，远古逻辑系统正在崩溃。
Using Traceability Matrices, you can query on use cases not yet traced to test requirements (answering the question How do you know that the entire system functionality is tested?).
使用TraceabilityMatrices，你能够在仍未追踪到测试需求的用例上查询(回答了“你怎样知道整个系统功能被测试？”这个问题)。
Using Traceability Matrices, you can query on use cases not yet traced to test requirements (answering the question How do you know that the entire system functionality is tested?).
使用TraceabilityMatrices，你能够在仍未追踪到测试需求的用例上查询(回答了“你怎样知道整个系统功能被测试？”这个问题)。
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