基于本体的智能答疑系统的研究与实现

自动答疑是现代远程教学系统中一个重要组成部分,然而目前的自动答疑系统大多以关键词匹配为基础,忽视了关键粤本身所含的语义信息、查询效率和结果不能满足用户的需要。提出了一个基于本体的智能答疑系统,利用本体中概念规范、语义关系明确的特点,将用户的问题查询请求进行语义上的扩展,增加了对语义信息的理解,有效地提高了查询的准确性。     

基于常见问题集FAQ的智能答疑系统

智能答疑系统是目前问答系统研究领域的一个热点,它既能让用户用自然语言语句提问,又能为用户返回一个简洁准确的答案.常见问题集FAQ是智能答疑系统中的一个重要组成部分,本文提出了FAQ的形成与处理机制,从而在理论上提高了智能答疑系统的性能.     

一种实用智能答疑系统在现代远程教育中的应用

简要介绍了现代教育及答疑系统的应用,分析了目前答疑系统存在的一些问题,提出了一个实用的智能答疑系统的模型。通过XML技术组织答案知识库,利用基于统计的方法进行分词与匹配,有效地提高了查询的精度。通过对知识进行系统的分类以及与学员的交互,缩小了搜索范围和时间,提高了答案的命中率。     

基于Ontology的多Agent智能答疑系统模型研究

针对目前智能答疑系统在知识共享、知识重用以及问题求解查全率和查准率方面的不足,提出了基于Ontology的多Agent智能答疑系统模型。该模型首先需要建立基于Ontology的问题解答知识库,然后对用户输入的问题进行关键词拆分、本体交互和语义扩展等,并在问题解答库中进行查询,得到合适的问题答案。与同类答疑系统比较,在知识共享、知识重用以及问题答案的精确定位与表达有了较为明显的改进。     

光纤通信答疑系统的设计

一个良好的答疑系统,能够提高答疑工作的便捷性和及时性,增加师生之间和学生之间的互动,提高学生的自主性学习能力。该文设计的答疑系统具有前台搜索与后台解决问题两个功能,系统具有查询速度快、结果呈现一定的关键词相关顺序及智能化等特点。用户可以自由提问,系统将以极快的速度呈现出用户满意的答案。经过实验表明,此方法有较高的精度。     

基于领域本体智能答疑系统的设计

答疑系统是远程教育系统的重要组成部分,针对传统答疑系统功能相对简单而且无法得到理想的答案等特点,提出一种基于领域本体智能答疑系统的设计。文章首先提出智能答疑系统的模型,并进行领域本体和问句语料库的构建研究,同时利用分词处理和关键词扩展技术进行问句查询的扩展,最后通过语句相似度的匹配方法,提升系统查询的准确率。     

关于网上智能答疑系统研究的几点思考

答疑是教学过程的一个重要组成部分。本文就国内目前已有网上智能答疑系统的研究文献进行梳理分析,并在此基础上,提出网上智能答疑系统需在答疑的学习机制、实证研究、互动性及个性化服务等方面加强研究。     

基于Web的智能答疑系统的设计与实现

本文简单分析了目前智能答疑系统的现状,并指出了它们存在的不足;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。     

基于本体的智能答疑系统的研究与实现

答疑系统是现代远程教育不可缺少的一个组成部分.针对目前答疑系统在知识共享和问题求解精确性方面的不足,提出了一种基于本体的智能答疑系统模型.该模型对于学生输入的问句,利用浅层语义分析技术,首先生成问句向量,再利用SPARQL查询语言,在本体库中查找答案.分析与研究了该系统所涉及的关键技术,以计算机应用基础课程为例,构建课...     

基于智能符号回归的路径规划A*算法均衡控制方法

随着地图网站和在线导航系统的普及,多用户网络并发出行信息查询服务的需求日益增长。如何满足多用户并发路径查询效率需求,同时又使得路径查询精度可控,是网络地理信息服务的瓶颈技术问题。本文提出了一种多用户并发路径查询精度效率均衡控制方法,利用系统抽样和智能符号回归技术,根据动态变化的在线路径查询用户规模和系统响应效率容忍阈值,在经典的路径查询A*启发式算法基础上,根据大样本确定的路径查询严密算法和对应启发式算法得到的系统耗时比和精度比,实时自动确定启发式路径查询启发因子权重,有效平衡多用户并发路径查询的响应效率和精度损失,自适应地控制路径查询算法的精度和效率之间的平衡,在精度预先可控的前提下,最大限度地提升多用户并发路径查询效率,缩短用户的路径查询等待时间。     

求解初中代数方程的智能解题系统

介绍了一种用于初中代数方程解题辅导的新型智能系统的原理、实现流程和测试结果。该系统是由用户在远程终端输入题目，中心服务器运行系统程序完成各项功能。该系统的特点是：面向辅导、基于互联网、具有精确解，及解题成功率高。另外，该系统还保证用户和远程服务器之间具有良好的互动性。有利于信息的及时传递和反馈。     

User modelling and user adapted interaction in an intelligent tutoring system

User modelling and user-adapted interaction are crucial to the provision of true individualised instruction, which intelligent tutoring systems strive to achieve. This paper presents how user (student) modelling and student adapted instruction is achieved in FITS, an intelligent tutoring system for the fractions domain. Some researchers have begun questioning both the need for detailed student models as well as the pragmatic possibility of building them. The key contributions of this paper are in its attempt to rehabilitate student modelling/adaptive tutoring within ITSs and in FITS's practical use of simple techniques to realise them with seemingly encouraging results; some illustrations are given to demonstrate the latter.     

A Knowledge-Based Approach to Effective Document Retrieval

This paper presents a knowledge-based approach to effective document retrieval. This approach is based on a dual document model that consists of a document type hierarchy and a folder organization. A predicate-based document query language is proposed to enable users to precisely and accurately specify the search criteria and their knowledge about the documents to be retrieved. A guided search tool is developed as an intelligent natural language oriented user interface to assist users formulating queries. Supported by an intelligent question generator, an inference engine, a question base, and a predicate-based query composer, the guided search collects the most important information known to the user to retrieve the documents that satisfy users' particular interests. A knowledge-based query processing and search engine is devised as the core component in this approach. Algorithms are developed for the search engine to effectively and efficiently retrieve the documents that match the query.     

知识界面在NKI中的应用

国家知识基础设施(NKI)构建存放大量的多学科的专业知识的知识服务器,提供知识服务。为了在用户和知识服务器之间建立有效的知识查询通道,需要设计一种知识界面。该文介绍设计和实现一种新颖的基于自然语言的知识界面。这一知识界面的特点是:(1)知识查询不依赖于特定用户、不依赖于特定查询方式和不依赖于特定查询内容;(2)用户与知识服务器的对话可以是上下文相关的,这为用户连续查询知识提供方便。     

智能教学系统NKI-Tutor的知识查询设计

NKI-Tutor是国家知识基础设施面向应用的智能教学系统，其功能是将NKI丰富的知识传授给用户。知识查询是NKI-Tulor给用户提供的一种查询式学习模式。该文研究如何通过NKI-Tutor的知识查询界面实现用户与智能教学系统的交互而获得所需知识，提出了基于自然语言理解的知识查询方法，用于构造和实现NKI-Tutor中用户查询知识的交互界面。该方法包括3方面内容：(1)分析用户的知识查询形式，采集用户查询句型模板；(2)根据用户查询的知识特征，把知识查询映射到概念．关系模型上；(3)通过智能分词和模糊匹配构造查询结果。     

Adaptive systems: from intelligent tutoring to autonomous agents

Computer systems which can automatically alter aspects of their functionality or interface to suit the needs of individuals or groups of users have appeared over the years in a variety of guises. Most recently, attention has focused on intelligent interface agents, which are seen as specialised, knowledge-based systems acting on behalf of the user in some aspect of the interaction. Similar requirements for automatic adaptation have been noted in intelligent tutoring systems, natural-language systems and intelligent interfaces. The paper brings together the research which has emanated from a number of backgrounds, and provides a unifying perspective on adaptive systems in general. An architecture for adaptive systems and a methodology for their development are presented. The paper also describes software support for producing adaptive systems, and offers some experimental evidence to justify both the desirability and feasibility of exploiting an adaptive system approach to human-computer interaction     

Student modelling in intelligent tutoring systems

Student modelling is a special type of user modelling which is relevant to the adaptability of intelligent tutoring systems. This paper reviews the basic techniques which have been used in student modelling and discusses issues and approaches of current interest. The role of a student model in a tutoring system and methods for representing information about students are discussed. The paper concludes with an overview of some unresolved issues and problems in student modelling.Electric Brain Company     

Towards an Intelligent Tutoring System Architecture that Supports Remedial Tutoring

For successful teaching to take place an intelligenttutoring system has to be able to cope with anystudent errors that may occur during a tutoringinteraction. Remedial tutoring is increasingly viewedas a central part of the overall tutoring process, andrecent research calls for adaptive remedial tutoring. This paper discusses the issues of remedial tutoringthat have been proposed or implemented to supportefficient remedial tutoring. These issues serve touncover any underlying principles of remediation thatgovern remedial tutoring with intelligent tutoringsystems. In order to incorporate these principles ofremediation into intelligent tutoring systemsdevelopment processes this paper continues with thedevelopment of a model that can be employed in thedevelopment of an intelligent tutoring system that iscapable of offering remedial tutoring according tothese principles. This model is a formalisation ofremedial interventions with intelligent tutoringsystems. To demonstrate how the model can be employed indeveloping an intelligent tutoring system, INTUITION,the implementation of an existing business simulationgame, has been developed. This paper concludes with anillustration of how the model for remedial operationsprovides for remedial tutoring within INTUITION. Theevaluation of INTUITION shows that the model forremedial operations is a useful method for providingefficient remedial tutoring.     

Empirical Derivation of a Sequence of User Stereotypes for Language Learning

The work described here pertains to ICICLE, an intelligent tutoring system for which we have designed a user model to supply data for intelligent natural language parse disambiguation. This model attempts to capture the user's mastery of various grammatical units and thus can be used to predict the grammar rules he or she is most likely using when producing language. Because ICICLE's user modeling component must infer the user's language mastery on the basis of limited writing samples, it makes use of an inferencing mechanism that will require knowledge of stereotypic acquisition sequences in the user population. We discuss in this paper the methodology of how we have applied an empirical investigation into user performance in order to derive the sequence of stereotypes that forms the basis of our modeling component's reasoning capabilities.