使用CIDOC CRM构建建筑领域非遗知识本体

非物质文化遗产是人类文明和历史文化的宝贵资源。运用本体技术可以实现非遗资源数字化管理,有利于非遗资源的保护、利用和共享。项目首次将文物保护领域的本体框架CIDOC CRM用于中国传统木结构建筑营造技艺这一非遗领域,并结合建筑领域的特性对CIDOC CRM模型结构进行选择和扩充,定义建筑领域非遗知识本体的概念类及其属性,并在实例化过程中运用TextRank算法处理文本语料,实现本体实例的扩充,将本体模型进行数据映射,存入Neo4j图数据库中,以知识图谱的形式实现可视化展示。实验表明：运用上述方法构建传统建筑非遗知识本体模型是可行的;创建的本体能将各种碎片化知识有效地连接在一起。该方法可用于对领域知识进行管理,将在建筑领域的非遗数字化保护和合理利用方面起到重要作用。     

基于本体的设备维护知识表示研究*

为满足设备维护领域知识数字化表示的需求,根据设备维护领域知识的特点,将本体引入到该领域的知识表示中。通过对设备维护资源构成的分析,以设备维护知识中维修经验知识表示为例,分析其概念和属性关联关系,设计了维护案例本体表示方法。采用OWL对维护案例本体进行统一的形式化描述和表示,较好地解决了维修经验知识的共享与重用难题。研究提出的维修经验知识表示方法已在某大机组群监测系统中得到成功应用。     

面向数字化系统互操作的知识表示技术研究

复杂产品多学科协同设计需求的增长,对产品设计的协同环境和功能互操作提出了更高的要求,为了解决异构系统间信息共享问题,采用基于本体的知识表示方法来对数字化系统进行知识的描述。针对数字化系统互操作的需求,结合数字化系统互操作的信息模型与功能模型,提出了一种基于OWL-S的支持互操作的知识表示方法,并在此基础上实现了原型系统。     

“互联网+”时代教育出版数字化发展思路探讨

自从进入“互联网+”时代，教育出版行业便深受影响。新时期背景下，教育出版行业意识到“互联网+”的发展，在一定程度上已经改变了人们的阅读习惯及方式，这给传统出版行业造成了严重冲击，进而导致传统教育出版行业难以保障教育出版的有效性。鉴于此，文章从“互联网+”视角，分析“互联网+”时代教育出版数字化发展的有效思路，针对教育出版面临的主要问题，提出了一些有效的发展策略，希望能促进教育出版数字化发展，真正拓展教育出版渠道，提高教育出版效率，为我国教育出版行业长足发展保驾护航。     

多媒体系统软件平台技术简介

面对信息时代知识经济的崛起,多媒体与网络技术飞速发展,尤其多媒体应用技术更是渗透到各行各业、千家万户。多媒体能改变信息的包装,实现知识信息数字化,为人们获得知识信息提供极大的方便和无穷的乐趣,因此多媒体技术在教育、出版、设计、展览、广告、娱乐等行业大...     

业界周讯

广东搭建数字化出版平台广东省数字化改造文化产业的时间表已经浮现:力争在10年之内,使广东成为国内数字出版产业发展的重要基地。到2010年,广东省将完成传统出版生产流程的数字化再造、城市综合信息门户网站建设、广东知识资源智能化数据库建设和数字图书、报纸、期刊、音像、管理等公共服务平台建设等示范项目。     

基于知识图谱的老年教育知识库系统设计与实现

在老年教育建设过程中,将信息技术与老年教育特点相结合,为提高老年教育过程中大量的数据、知识存储和查询效率,设计了一种基于知识图谱的老年教育知识库系统.系统以知识图谱为核心,通过对老年教育不同角色的业务进行分析并设计本体,将多领域和多类型的数据通过本体映射,完成知识图谱构建,将繁杂无序的数据形成具有内在多种关联的知识库,并为学员和教师提供在线的知识管理和知识服务功能.与传统的数据管理方式相比,知识检索和信息获取效率得到有效提高.     

基于本体的几何学知识获取及知识表示

文中研究了基于本体的几何学知识获取,并运用此方法获取几何学领域中的类、属性、关系及公理等;同时,研究了基于本体的知识表示,并将几何学知识转化为该领域本体,用RDF/OWL的形式进行描述.在此基础上构建了一个可共享、可重用、可扩展的几何学本体,形成了一套较完整的几何学知识获取和知识表示体系,将其应用于建立几何学知识库,可大大提高知识搜索和知识推理的效率,并为几何学专家系统、几何学信息检索、几何学教育系统、自然语言理解等领域提供智能基础.     

天津轻轨应急预案管理系统研究与设计

应急预案是描述应急响应事件处置的领域知识,是应急管理系统的基础,应急预案数字化是解决计算机理解和识别预案问题。通过对天津轻轨应急预案文本系统分析和研究,以重用ABC本体模型和基于工作流等技术基础上,实现应急预案本体,并设计出天津轻轨应急预案管理系统,以提高天津轻轨突发事件的应急处置能力,更好地保障城市轨道交通的安全运营。     

数字与微化课程也优化——试论信息技术微型课程的生态创新与发展

针对当前信息量日益增大以及信息技术学科知识本体的繁冗性,而诞生的数字化环境下的微型课程形态,成为备受关注的一个新的研究课题。作为一种新的知识获取途径,微型课程具有复杂性知识表达能力强、灵活性好、知识的可吸收率高以及与真实世界联系密切等特点,有效弥补了传统课程知识表达的不足。这种数字化环境下的微型课程形态,既可以作为独立的“微型课程学习包”又可以承担“课程补丁”的功效。对于它的认识和研究,将成为解决知识获取瓶颈的有效方法。     

Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning

Recommender systems in e-learning domain play an important role in assisting the learners to find useful and relevant learning materials that meet their learning needs. Personalized intelligent agents and recommender systems have been widely accepted as solutions towards overcoming information retrieval challenges by learners arising from information overload. Use of ontology for knowledge representation in knowledge-based recommender systems for e-learning has become an interesting research area. In knowledge-based recommendation for e-learning resources, ontology is used to represent knowledge about the learner and learning resources. Although a number of review studies have been carried out in the area of recommender systems, there are still gaps and deficiencies in the comprehensive literature review and survey in the specific area of ontology-based recommendation for e-learning. In this paper, we present a review of literature on ontology-based recommenders for e-learning. First, we analyze and classify the journal papers that were published from 2005 to 2014 in the field of ontology-based recommendation for e-learning. Secondly, we categorize the different recommendation techniques used by ontology-based e-learning recommenders. Thirdly, we categorize the knowledge representation technique, ontology type and ontology representation language used by ontology-based recommender systems, as well as types of learning resources recommended by e-learning recommenders. Lastly, we discuss the future trends of this recommendation approach in the context of e-learning. This study shows that use of ontology for knowledge representation in e-learning recommender systems can improve the quality of recommendations. It was also evident that hybridization of knowledge-based recommendation with other recommendation techniques can enhance the effectiveness of e-learning recommenders.     

基于知识点本体的学习资源框架设计

针对目前语义缺失,缺少可重用性、互操作性、共享性的学习资源现状,提出将知识点本体引入学习资源库功能模型的构建和学习知识的表达,模型中采用KDD技术对领域学科知识点的内在联系及层次关系进行分析和研究．并构建领域知识点本体模型,为学习资源适应个性化学习提供语义基础,实现资源的共享和重用。     

基于Web2.0和本体检索的个性化E-learning系统研究与开发

针对当前E-learning系统中存在着堆砌教学资料和学习内容单一、个性化不足等问题,设计一个基于Web2.0和本体检索技术的个性化E-learning系统,通过应用Ajax和RSS聚合技术以及Ontology本体技术,使得该系统能根据学习者的知识结构、学习目标、学习风格、偏好等特征信息提供适应学习者的教学方法和学习资源,营造个性化的网络学习环境。实验结果表明该系统能有效促进学生网络学习的效率,满足学生个性化学习的需求。     

实例驱动的自适应本体学习

针对知识管理中本体构建存在的问题,将聚类算法与ODP（Open Directory Project）目录有机结合,给出了一种基于知识资源元数据的自适应本体学习方法。根据元数据对文档进行聚类形成本体概念,将生成的概念分别映射到ODP中确定概念间的层次关系,生成初始本体;根据内聚性和相关性的变化进行自适应本体学习,实现本体更新和概念丰富,以及时跟踪知识的变化。提出的自适应本体学习方法能够很好地反映研究领域的演变过程和发展趋势,满足知识型组织进行知识管理和研究人员共享知识的需求。实验结果表明了方法的有效性。     

《数据结构》课程知识本体构建研究

介绍当代移动学习的特点和语义网本体技术,提出利用本体技术来适应移动学习的片段式学习方式要求,并以《数据结构》课程为例阐述课程知识本体库的具体构建过程．为其在移动学习系统中的应用打下研究基础。     

Distributed Knowledge Management in eLearning

With the wide application of Internet in elearning, the requirement of reusable, sharable learning objects and adaptive learning strategies becomes common ground. Traditional methods of Web resources publishing and managing such as free publishing or building application systems for special purposes are not good at fast discovering and aggregating knowledge. This paper discusses Meta-data structure in elearning, which facilitates searching, managing and linking granules of learning contents. Applying Web services and UDDI techniques, a system of knowledge management on Web based on Meta-data is proposed and some questions in application are discussed.     

本体在E learning系统中的应用研究*

探讨了Elearning及本体,提出了基于本体的Elearning系统层次结构模型,并重点研究了本体在其中的应用：用于描述学习材料语义的内容本体,用于定义学习材料上下文的上下文本体以及用于在学习课程中组织学习材料的结构本体。     

本体在E-learning系统中的应用研究

探讨了E-learning及本体,提出了基于本体的E-learning系统层次结构模型,并重点研究了本体在其中的应用：用于描述学习材料语义的内容本体,用于定义学习材料上下文的上下文本体以及用于在学习课程中组织学习材料的结构本体。     

A language learning support system using course-centered ontology and its evaluation

This paper presents a course-centered ontology for assisting learning support systems to embody the relations among knowledge points and also among the learning materials for those knowledge points. An “individual-class-individual” ontology design (first an individual-class design, then an innovative design about relations among bottom individuals), was applied to the construction of a course-centered ontology for an existing Japanese grammar course. Furthermore, a customizable language learning support system was built to manipulate the course-centered ontology to provide an interface for the learning objects arrangement which displays the visual representation of knowledge points and their relations. The intention underlying the development of the system is to encourage instructors to orient their teaching materials to specific knowledge points and even directly to relations between knowledge points. With these orientations, the learning support system is able to provide an environment in which learners can readily distinguish between related knowledge points. Finally, based on the result of a preliminary evaluation, a study to explore the impact of learning styles and learning habits on learning performance was conducted to further evaluate our ontology-based learning support system. The results of the study suggest three main points: (a) the experimental students who learned with our system achieved significantly better learning achievement than those who just did self-study with textbooks after studying the same target contents for 60 mins; (b) the learning achievement of experimental group was not related to either their learning style in Sequential/Global dimension or their habit of “learning from comparison”; (c) in terms of the learning perception of experimental group, compared to “Sequential learners”, most “Global learners” had a stronger feeling that the comparison function is useful in improving their learning performance, and the learners who don't habitually “learning from comparison” were more likely to suffer from lack of the attention and feel more pressure than those who do habitually “learning from comparison”.     

Ontology learning: state of the art and open issues

Ontology is one of the fundamental cornerstones of the semantic Web. The pervasive use of ontologies in information sharing and knowledge management calls for efficient and effective approaches to ontology development. Ontology learning, which seeks to discover ontological knowledge from various forms of data automatically or semi-automatically, can overcome the bottleneck of ontology acquisition in ontology development. Despite the significant progress in ontology learning research over the past decade, there remain a number of open problems in this field. This paper provides a comprehensive review and discussion of major issues, challenges, and opportunities in ontology learning. We propose a new learning-oriented model for ontology development and a framework for ontology learning. Moreover, we identify and discuss important dimensions for classifying ontology learning approaches and techniques. In light of the impact of domain on choosing ontology learning approaches, we summarize domain characteristics that can facilitate future ontology learning effort. The paper offers a road map and a variety of insights about this fast-growing field.