基于Web的智能教学系统模型

智能教学系统是当前计算机应用的重要领域之一，文中主要研究在国家知识基础设施(NKI)支撑下的基于Web的智能教学系统模型：NKI-Tutor。NKI-Tutor包括七个模块：学生模型、教学模型、交互模型、NKI知识库、专家模型、出题模块和模拟工具，其主要特点是：(1)教学内容覆盖多个学科知识，且是动态的知识库；(2)交互模块给教师提供可操作的教学策略描述语言，便于教师在系统中设计个性化的教学策略。     

C-MCAI系统的设计与实现

C-MCAI系统是C语言程序设计的多媒体辅助教学系统，该系统主要由知识体和习题库两部分组成。采用从三个不同的抽象层次逐步求精的软件设计思想构造了系统的知识体；结合数据库系统的查询、管理功能和多媒体创作工具的多媒体集成、交互功能实现了习题库的多媒体构造和查询。     

基于贝叶斯网络的XML文档查询模型

目前XML查询语言及查询界面对Web用户过于复杂，该文描述了一种XML文档索引机制，在此基础上建立了一个通用的贝叶斯网络查询模型。用户只需在交互界面输入自然语言描述的查询，系统就能对其实现基于语义的构造，由它生成多个结构化查询；对这些查询建立贝叶斯网络，计算查询在给定文档下的概率，选择概率最大的前3个查询提交给系统执行。     

一种面向领域本体的教学策略研究方法

教学策略是智能教学系统研究的一个核心问题。论文提出一种基于领域本体的教学策略研究方法,该方法主要包括微教学策略、宏教学策略和教学策略描述语言(TSDL),在领域本体抽象层上实现多个学科教学和个别化教学。该方法在智能教学系统NKI-Tutor中已实现。     

基于Web的智能教学系统的研究与实现

针对当前智能教学系统存在的不足,设计了一个基于WEB的智能教学系统模型。主要论述了系统的功能结构,学生模型和教师模型的构造以及知识表示方法和推理机运用知识进行推理的过程,侧重于方法与策略的研究与应用。旨在通过本系统的实现,为网络学习中的用户提供个性化、智能化的学习内容与指导。     

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。     

一种基于Agent结构的地理信息系统

把智能体(Agent)技术引入地理信息系统中,用以增强地理信息系统的人机交互能力和多信息源的可扩展性.用户的问题与用户的查询目标和领域知识相关,因此,交互界面智能体能通过匹配知识库的过程引导用户细化问题,最终提供给用户满意的答案.而且,基于智能体体系结构的建立能够更好地集成各种异构信息源,由于各种异构信息源的集成,所以可以提供给用户数量更多和质量更高的信息.此外还详细描述了一个基于智能体结构的原形系统GXGIS.     

基于决策树算法的可用性评估平台的实现

可用性是体现产品质量和市场竞争力的重要因素，可用性评估可以考察软件的效率、有效性、用户满意度，该文研究开发的可用性评估平台为软件开发过程的可用性评估提供专家知识支持。为了使可用性评估平台根据已有知识向用户提供具有价值的建议，使用改进后的启发式归纳分类算法：ID3决策树算法。根据对已有知识的信息熵计算，建立多叉决策树，然后利用交互过程中用户选择的节点信息得到用户的知识分类，向用户提供知识建议。系统在交互过程中，通过层层深入的交互方式，不断引导用户进行思考，做出选择，细化知识内容，排除冗余信息影响，明确具体属性值，实现主动的智能交互。通过改进的ID3决策树算法配合分层交互的方法建立的可用性评估平台系统能够有效地帮助用户完成软件的可用性评估工作，受到用户的认可。     

一种基于web技术的分布式智能教学系统的实现方法

基于ｗｅｂ数据库技术,以 ＡＳＰ的 ＡＤＯ技术设计人机交互环境,构造了一种分布式智能教学系统（ ＩＴＳ）的实现方法,解 决了分布式智能教学系统知识库、推理机与诊断规则等的实现问题。探讨了分布式ＩＴＳ网上知识获取的实现方法。     

A formal framework for query decomposition and knowledge integration in data warehouse federations

A federation of data warehouses is understood as a set of data warehouses, which can be processed as a whole in the logic level. Physically, the federation does not gather data into one place. This paper presents a formal framework for data and knowledge processing in data warehouse federations. The management system for a data warehouse federation consists of an user interface enabling presentation of user queries, a program for query decomposition and a program for integrating knowledge coming from different data warehouses as the answers to a user query. We propose a model for query decomposition process and knowledge integration. It contains also the algorithm for knowledge inconstancy processing. This kind of inconsistency often occurs since very often the knowledge extracted from different data warehouses refers to the same subject, but is not consistent.     

Using WordNet and lexical operators to improve Internet searches

A natural language interface system for an Internet search engine shows substantial increases in the precision of query results and the percentage of queries answered correctly. The system expands queries based on a word-sense-disambiguation method and postprocesses retrieved documents to extract only the parts relevant to a query     

Effects of query complexity and learning on novice user query performance with conceptual and logical database interfaces

Users see the database interface as the database system. A good interface enables them to formulate queries better. The semantics communicated through the interface can be classified according to abstraction levels, such as the conceptual and logical levels. With the conceptual interface, interaction is in terms of real-world concepts such as entities, objects and relationships. Current user-database interaction is mainly based on the logical interface, where interaction is in terms of abstract database concepts such as relations and joins. Many researchers argue that end users will perform better with the conceptual interface. This research tested this claim, as well as the effects of query complexity and learning, on the visual query performance of users. The experiment involved three tests: an initial test, a retention test and a relearning test. The results showed that, for complex queries, conceptual interface users achieved higher accuracy, were more confident in their answers, and spent less time on the queries. This is persistent across retention and relearning tests.     

Query-by-Gaming: Interactive spatio-temporal querying and retrieval using gaming controller

Spatio-temporal querying and retrieval is a challenging task due to the lack of simple user interfaces for building queries despite the availability of powerful indexing structures and querying languages. In this paper, we propose Query-by-Gaming scheme for spatio-temporal querying that can benefit from gaming controller for building queries. By using Query-by-Gaming, we introduce our spatio-temporal querying and retrieval system named as GStar to interactively build subsequent spatio-temporal queries to determine if a state is directly reachable from current state and eventual spatio-temporal queries to know whether a spatial state is reachable from a current state. Queries are built using features of gaming controller by displaying the original video frames rather than on a graphical interface using a mouse or a keyboard. GStar has three main components: building the query, searching and retrieval of clips, and displaying query results. The queries are applied to an indexing structure called semantic sequence state graph (S³G) and results of the query are displayed dynamically to provide timely feedback to the user. Experimental results and user interface are provided for a tennis video database. Users define desired game state (player and ball position) using an interactive interface at multiple points in time and GStar automatically retrieves all rallies that contain both states. Finally, the user interface evaluation comparing gamepad-based interface and mouse interface for spatio-temporal querying has been studied.     

QBD*: a graphical query language with recursion

A system to query databases using diagrams as a standard user interface is proposed. The system, called Query by Diagram* (QBD*), makes use of a conceptual data model, a query language on this model, and a graphical user interface. The conceptual model is the entity-relationship model. The query language, whose expressive power allows recursive queries, supports visual interaction. The main characteristics of the interface are ease of use and the availability of a rich set of primitives for schema selection and query formulation. The expressive power of QBD* and G⁺, which are the only languages allowing recursive queries to be expressed graphically are compared     

Visual spatio-temporal function-based querying

Visual interfaces are very important for human interactions in cyberworlds. Visual spatio-temporal querying should be one of the basic tools for data mining and retrieval in cyberworlds. In this paper, we propose a novel function-based query model for arbitrary shape spatio-temporal querying. The queries are defined as geometric shapes changing over time. In our model, data are interpreted geometrically as multidimensional points with time dimension or as moving points. The queries are formulated with geometric objects and operations over them to form the query solid changing over time. The proposed query model allows us to pose arbitrary shape spatio-temporal range queries. With the uniform geometric model we integrate visual mining and querying of time-dependent data employing 3D visualization tools. It allows for creating an intuitive visual interface using 2D projections of 3D query shapes. Our approach combines visualization of spatio-temporal data with visualization of the range query formulation employing very compact function-based query model. The implemented visual query system and its visual interface are proposed and described. An example of application of the system in analysis of simulation results in molecular dynamics is considered.     

Word segmentation based on database semantics in NChiql

In this paper a novel word-segmentation algorithm is presented to delimit words in CHinese natural language queries in NChiql system,a Chinese natural language query interface to databases.Although there are sizalbe literatures on Chinese segmentation.,they cannot satisfy particular requirements in this system,The novel word-segmentation algorithm is based on the database semantics,namely Semantic Conceptual Model(SCM) for specific domain Knowledge,Based namely Semantic COnceptual Model(SCM) for specific domain knowledge,Based on SCM,the segmenter labels the database semantics to words directly,which eases the disambiguation and translation(from natural language to database query)in NChiql.     

Processing top-<Emphasis Type="Italic">N</Emphasis> relational queries by learning

A top-N selection query against a relation is to find the N tuples that satisfy the query condition the best but not necessarily completely. In this paper, we propose a new method for evaluating top-N queries against a relation. This method employs a learning-based strategy. Initially, this method finds and saves the optimal search spaces for a small number of random top-N queries. The learned knowledge is then used to evaluate new queries. Extensive experiments are carried out to measure the performance of this strategy and the results indicate that it is highly competitive with existing techniques for both low-dimensional and high-dimensional data. Furthermore, the knowledge base can be updated based on new user queries to reflect new query patterns so that frequently submitted queries can be processed most efficiently. The maintenance and stability of the knowledge base are also addressed in the paper.     

Fragmenting relations horizontally using a knowledge-based approach

In distributed DBMSs, one major issue in developing a horizontal fragmentation technique is what criteria to use to guide the fragmentation. The authors propose to use, in addition to typical user queries, particular knowledge about the data itself. Use of this knowledge allows revision of typical user queries into more precise forms. The revised query expressions produce better estimations of user reference clusters to the database than the original query expressions. The estimated user reference clusters form a basis to partition relations horizontally. In the proposed approach, an ordinary many-sorted language is extended to represent the queries and knowledge compatibly. This knowledge is identified in terms of five axiom schemata. An inference procedure is developed to apply the knowledge to the queries deductively