研究了智能答疑系统中的问题分类。
Research of intelligent question answering model based on ontology;
本文围绕智能答疑系统一些关键技术进行了研究分析。
This paper focuses on some kernel techniques on Intelligent Question answering system.
并通过一个具体的实例介绍了智能答疑系统的功能与特点。
It introduces the intelligent system's functions and characters by an example.
摘要：构建知识库是搭建分布式环境下智能答疑系统平台的关键环节。
Absrtact: a distributed intelligent question answer system is a platform sharing resource among the sites.
针对以上缺点，本文给出一个应用语义网络原理构筑起来的智能答疑系统。
To solve this problem, this paper presents an agent-based intelligent tutoring system by applying the semantic-net principle.
构建了一种集人工答疑、智能答疑和联合答疑于一体的新型远程答疑系统。
A new remote answering system which combines the functions of manual answering, intelligent answering and united answering, is proposed.
它是中文智能答疑系统的一项基本性技术，可以说，没有分词技术任何中文答疑系统都不具有智能性。
This paper mostly researches Chinese word segmentation, because it is a basal place in intelligent answering system.
利用当前比较先进的自然语言分析技术、全文检索技术、数据挖掘技术等，设计了比较全面的网络课程的智能答疑系统。
Using the present advanced technologies such as nature language, full-text searching and data mining, this paper designed a full-round intelligent question-answer system of network course.
在此基础上提出了一个智能答疑系统的结构模型，主要介绍系统中FAQ库的自动形成机制，并给出系统中的关键实现技术。
It presents the structural model of a new intelligent answer-question system, introduces the automatic formation mechanism of the FAQ library, and gives the key techniques of realization.
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。
The innovative solution has been already applied to the natural language intelligent network Question Answering system. The application achieved well results.
课题重点研究了网络考试系统中智能组卷的方法和实时、非实时网络答疑系统的实现途径。
The item study the methods of composing test paper of exam on web and the way to realize real-time or unreal-time answer 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。
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.
本系统模型实现了答疑系统的语义理解，提高了现有网络答疑系统的效率，并具有一定的智能性。
The system model realizes semantic understanding of Question Answer system improving efficiency of the present Question Answer system and with certain intelligence.
本系统模型实现了答疑系统的语义理解，提高了现有网络答疑系统的效率，并具有一定的智能性。
The system model realizes semantic understanding of Question Answer system improving efficiency of the present Question Answer system and with certain intelligence.
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