网络学习与知识表示

为了更有效地支持网络学习、支持学生通过机器进行自主学习,必须有一套完整的知识描述机制,为此探讨在一个课程知识体系或知识领域内知识的描述方法和实现方法。     

On the Relationship between the Evolution of Technological Firms and Their Knowledge Development Regimes

Scientific and technological knowledge is increasingly understood as an endogenous key factor to explain the competitiveness and development of industries and individual firms[1]. An essential cornerstone is therefore the notion of the firm as an organization of capabilities and accumulation of knowledge of how to do things[2]. Much of the recent theoretical work on industrial dynamics has hence focused on the emergence and development of new firms in knowledge and technology intensive industr…     

广义科普知识的划界与分层

基于对科普知识的广义理解,将科普知识分为核心层、中间层与外围层三个层面。核心层是在"学院科学"理念下的简化的科学知识,遵守默顿的CUDOS规范;中间层是与生产生活相结合的后学院科学知识,遵守齐曼的PLACE规范;外围层是与社会文化相结合的生活科学知识,遵守BASIC规范,且各层次从目的、理念、内容、模式、物化表现等方面都各具特点。这三个层面的科普知识从核心到外围没有绝对界限,但从"纯净"的基础科学知识到社会、文化因素渗透的趋势越来越强。科普知识的细分与深层剖析为更好地开展科普工作提供理论参考。     

在线学习共同体知识创新评价指标体系设计

将在线学习共同体（OLC）的学习与知识创新联系起来,可使OLC研究进入新阶段。知识创新属于高层次的认知目标,目前尚无评价框架对基于OLC学习所产生的知识创新水平进行评价。在此以学习目标分类学、创造性思维理论、交互质量水平、SOLO层次模型、创新扩散理论等为基础,构建了一个较为全面的OLC知识创新评价指标体系。该指标体系可以作为对OLC知识创新进行内容分析的类目,也可以作为对OLC知识创新水平进行评价的评价体系。     

A Study of the Techniques of Automatic Abstracting and Knowledge Acquisition Systems

A Study of the Techniques of Automatic Abstracting and Knowledge Acquisition Systems     

融合先验知识的支持向量机回归方法

类似大多数基于统计的纯数据驱动机器学习方法一样,标准支持向量机回归也是建立在对纯样本数据学习基础上的,需要足够多标记好的样本数据才能保证模型的性能,当样本数据集趋于无穷大时,学习模型也越趋向于真实模型。然而在实际应用中,这个条件往往很难得到满足。如果能将样本数据的先验知识融合到支持向量机回归中,就可以弥补样本不足的缺陷。本文提出一种融合先验知识的支持向量机回归方法,给出了理论推导的一般形式,并通过实验证明该方法的有效性。     

共享学习模式下知识服务云平台的构建研究

通过剖析知识服务的内涵和特征,梳理知识服务中存在的问题,结合云计算的特性,给出共享学习模式下知识服务的新模式。构建了知识服务云平台体系结构,设计了知识资源层、知识融合层、知识服务层、运营服务与计费保障体系、客户应用层5个知识服务功能模块,实现了知识资源的共享和协同。     

Semantic Knowledge Management for Education

ldquoSemantic technologiesrdquo are touted as the next big wave in educational technology and as the solution to many problems in this arena. Interdisciplinary work between the fields of knowledge management (KM) and educational technology (ET) is booming. But the crop of actual systems and semantically enhanced learning objects is still meager, maybe because KM and EL are lacking a consensus on the underlying notions, e.g., of ldquosemantics,rdquo yielding specific problems in their interplay. In this paper, we look at semantic educational technologies and draw conclusions for their approach in KM. In particular, we (re)evaluate the notions of semantics, knowledge, and learning; their role for learning materials in ET; and how they interact with the contexts involved in the learning/teaching process. Based on this, we distill a list of conditions the underlying knowledge representation format must fulfil to support these. As these conditions are still rather abstract, we show how they can be realized in a concrete language design, taking in our open mathematical documents format OMDoc as a point of departure.     

Knowledge triple extraction in cybersecurity with adversarial active learning

Aiming at the problem that using pipeline methods for extracting cybersecurity knowledge triples may cause the errors propagation of entity recognition and did not consider the correlation between entity recognition and relation extraction,and training triple extraction model lacked labeled corpora,an end-to-end cybersecurity knowledge triple extraction method with adversarial active learning was proposed.For knowledge triple extraction,the conventional entity recognition and relation extraction were modelled as sequence labeling task through joint labeling strategy firstly.And then,a BiLSTM-LSTM-based model with dynamic attention mechanism was designed to jointly extract entities and relations,forming triples.Finally,with adversarial learning framework,a discriminator was trained to incrementally select high-quality samples for labeling,and the performance of the joint extraction model was continuously enhanced by iterative retraining.Experiments show that the proposed joint extraction model outperforms the existing cybersecurity knowledge triple extraction methods,and demonstrate the effectiveness of proposed adversarial active learning scheme.     

科学系统地设计教材的知识应用结构

传统教材内容的结构基本上是按科学逻辑顺序编排的知识应用结构，因而它的主要功能是传授知识。一本具有传授知识的培养能力双重功能的教材，应具有经过`科学系统设计的知识系统结构和适应应用结构。     

Intelligent Knowledge Recommendation Methods for R&D Knowledge Portals

The personalization in knowledge portals and knowledge management systems is mainly performed based on users' explicitly specified categories and keywords. The explicit specification approach requires users' participation to start personalization services, and has limitation to adapt changes of users' preference. This paper suggests two implicit personalization approaches: automatic user category assignment method and automatic keyword profile generation method. The performances of the implicit personalization approaches are compared with traditional personalization approach using an Internet news site experiment. The result of the experiment shows that the suggested personalization approaches provide sufficient recommendation effectiveness with lessening users'unwanted involvement in personalization process.     

基于过程的中学教师个人知识管理探究

中学教师作为社会上典型的知识工作者,知识是其生存和发展的重要资本。当前,部分中学教师虽然拥有丰富的知识,但在知识管理方面却存在不少问题。本文从中学教师个人知识管理存在的问题入手,在分析教师个人知识管理内涵的基础上,深入阐述教师实施个人知识管理的过程与方法,并提醒几个需要注意的事项,以期帮助教师实施有效的知识管理,提升个人价值和核心竞争力。     

An Analysis of Knowledge Sharing Approaches for Emerging-technology-based Strategic Alliances in Electronic Industry

Emerging technologies are now initiating new industries and transforming old ones with tremendous power. They are different games compared with established technologies with distinctive characteristics of knowledge management in knowledge-based and technological-innovation-based competition. How to obtain knowledge advantage and enhance competences by knowledge sharing for emerging-technology-based strategic alliances （ETBSA） is what we concern in this paper. On the basis of our previous work on emerging technologies＇ distinctive attributes, we counter the wide spread presumption that the primary purpose of strategic alliances is knowledge acquiring by means of learning. We offers new insight into the knowledge sharing approaches of ETBSAs - the knowledge integrating approach by which each member firm integrates its partner＇s complementary knowledge base into the products and services and maintains its own knowledge specialization at the same time. So that ETBSAs should plan and practice their knowledge sharing strategies from the angle of knowledge integrating rather than knowledge acquiring. A four-dimensional framework is developed to analyze the advantages and disadvantages of these two knowledge sharing approaches. Some cases in electronic industry are introduced to illustrate our point of view.     

Concept Lattices for Knowledge Management

The aim of the method presented in this paper is to support the acquisition of new knowledge and to enhance the interactions between knowledge workers. The approach chosen is to facilitate the sharing of those retrieval terms, which members of a community of practice have used to retrieve valuable information. The nature of information-seeking behaviour in on-line information sources is discussed and then the theory of formal concept analysis is introduced. It is subsequently shown how this theory can be applied to analyse the relations between documents and the retrieval terms that people use to access these documents.The result is a concept lattice that contains information on a community's information-seeking behaviour. The concept lattice uncovers relational and contextual information. Retrieval phrases are put into relational context depending on how they are associated by the documents that are of interest to a community of users. The contention made here is that such 'usage-based' structures will provide natural and intuitive access to information sources for communities of users. It is shown how this approach can be used to facilitate the sharing of the retrieval vocabulary to support the acquisition of new knowledge and to enhance the interactions within a community of practice.     

基于光并行计算的知识库系统及硬件支持系统

本文在分析知识库系统和光计算特点的基础上,提出了基于计算的知识库系统（KBSBOC）模型及其硬件支持系统,KBSBOC采用二进制矩阵表示知识,并用矩阵计算实现并行推理和学习,这种知识库操作全并行化,适合于光计算,KBSBOC硬件支持系统是光电混合系统,主要由主控机,知识存储体及光并行逻辑运算器构成,性能分析和实验结果表明KBSBOC及其硬件支持系统是有效的,合理的,它使解决迷宫问题的时间复杂性压缩到O(n).     

计算机网络基础知识在高校中的普及与策略研究

计算机网络基础知识,涵盖了基本Windows操作、如何防止计算机病毒的危害及对杀毒软件的具体设定与应用等。当今社会已全面进入网络时代,当代大学生有必要掌握一定计算机网络知识,对学习和生活提供有利帮助。文章主要探讨普及计算机网络基础知识对当代大学生的必要性,并在此基础上分析应注意的问题及有效学习策略。     

Interactive Human Intention Reading by Learning Hierarchical Behavior Knowledge Networks for Human‐Robot Interaction

For efficient interaction between humans and robots, robots should be able to understand the meaning and intention of human behaviors as well as recognize them. This paper proposes an interactive human intention reading method in which a robot develops its own knowledge about the human intention for an object. A robot needs to understand different human behavior structures for different objects. To this end, this paper proposes a hierarchical behavior knowledge network that consists of behavior nodes and directional edges between them. In addition, a human intention reading algorithm that incorporates reinforcement learning is proposed to interactively learn the hierarchical behavior knowledge networks based on context information and human feedback through human behaviors. The effectiveness of the proposed method is demonstrated through play‐based experiments between a human and a virtual teddy bear robot with two virtual objects. Experiments with multiple participants are also conducted.     

基于不完备知识的模糊本体构建(英文)

There exists widely incomplete knowledge all over the world, but incomplete knowledge still cannot be dealt with in the process of ontology construction. Hence, a method for fuzzy ontology construction based on incomplete knowledge is proposed. First, the calculation principle of the attribute weight of the ontology concept is presented, and the calculation function of the attribute weight is derived through experiments. Then, the membership degree of the incomplete individual to the concept is computed. Finally, the incomplete individual is classified according to the principle of the variable precision rough set model. The experimental results show that the average precision of the classification of the incomplete individuals is 81.7% when the common attributes are omitted and that it is difficult to classify the incomplete individuals correctly when the private attributes are omitted. This method is significant for handling incomplete knowledge in the process of ontology construction.     

"知识论"基础研究

知识是人类所创造的宝贵财富,但至今没有形成系统的知识理论.本文旨在提出和建立知识论的必要基础,给出知识的概念、定义、表示、度量、推理和决策规则.知识论的建立将为信息论-知识论-智能论的统一理论奠定坚实的基础,促进人们在更高的水平上利用信息和知识,研究、设计和应用各种智能机器.     

知识论:核心问题——信息-知识-智能的统一理论

知识是人类所创造的宝贵财富,但是至今还没有形成系统的知识理论.文[1]提出和建立了知识的初步基础,给出了知识的概念、定义、表示、度量、推理和决策规则.本文则试图在此基础上阐明信息与知识、知识与智能的关系,建立知识论的核心框架.作者相信知识论的建立将为信息论-知识论-智能论的统一理论奠定必要的基础,促进人们在更高的水平上利用信息和知识,研究、设计和应用各种智能机器.