概念获取的框架表征重述方法*

基于知识的问题求解需要一个丰富而相对完备的信念系统,尤其是当任务具有领域非限定特征时。经典知识工程关于知识获取、表示与使用的方法只能适应领域受限问题,因为它不是从概念发展的角度来建构概念系统的,面临着Framework Problem。针对认知心理学对概念系统发展与表征问题研究有一定的认知深度同时又缺乏系统构造与实现机制研究的情况,提出了一种基于框架表征的概念系统表征与发展方法,详细研究了概念在内的隐水平I、外显水平E1、外显水平E2和外显水平E3上的表征和发展过程。这一研究对于提高基于知识的系统推理能力和问题求解能力具有显著意义。     

基于Web的智能化课程网站设计关键技术与应用

建立了提高“概念类”课件智能化程度的设计理论和技术。给出了组织教学内容时涉及的实例引出、规则解释、问题生成、问题求解等基本教学功能的实现理论;在“教学知识”、“学生模型”、“领域知识”三者的有机结合上,采用结构化表示方法解决领域知识的表示问题,对通常所指的结构化表示进行了完善,使其能同时表示事物的静态结构和动态结构。建立了教学过程中“基本教学环节中例题和问题量的给定”、“问题调用时难度值和问题类型的给定”和“基本教学环节掌握度阈值的给出”等理论与技术问题。     

基于概念层次网络的知识表示与本体建模

知识表示是自然语言理解的重要基础。知识表示不统一、语义信息无法系统化利用是目前存在的亟待解决的问题。要解决这个问题,就要解决语义知识表示的问题。该文基于概念层次网络,描述了词语、句子和篇章层面的语义知识表示方法。基于文中描述的词汇层面的表示方法,构建了一个多语言本体知识库。该知识库的知识表示方法不仅可以为知识表示理论研究提供基础,还可以为自然语言处理相关领域的应用提供资源支持。     

基于需求分解的知识系统建模方法

通过对知识系统的需求分析及分解，将知识系统的知识划分为领域概念知识(概念本体)、系统知识(任务本体)、控制知识和解释知识四大部分，初步建立了各部分的实现框架和相应的策略，其中概念本体描述知识系统的静态知识，任务本体描述知识系统的动态知识。以一个简化农业种植结构配置知识系统为例，建立了系统的应用本体求解模型。这种基于需求分解的知识系统建模方法具有面向问题和应用、实用性强等优点。     

一种基于证据理论的概念树结构多Agent合作求解模型

本文针对多Agent系统中Agent之间的盲目交互可能产生的效率低下问题,提出了一种基于慨念树结构的多Agent合作求解模型.在这个模型中,各Agent基于自己的领域知识构造出概念树,通过Agent之间的合作,对概念树从根节点开始使用证据理论实现逐层聚焦,逐步缩小求解范围.为此,本文基于模态、逻辑和关系概念提出了一种面向可能解集的证据理论表示,并探讨了在多Agent环境下应用证据理论可能导致的若干问题.     

一种基于动态模糊集的概念学习模型

概念学习作为一种重要的数据分析方法,被广泛应用于模式识别、知识发现等领域。本文针对海量数据中的动态模糊数据,从DFL的角度出发,对动态模糊概念学习问题进行了深入的研究,提出了动态模糊概念的形式化表示方法、动态模糊概念格的构建方法。给出一个实验用例,验证相关算法的有效性。     

概念代数在本体合并中的应用

本体合并是本体集成的一种较为有效的方式,是用于解决本体异构以实现本体资源重用和共享的一种方法。引入概念代数以弥补本体的概念深度表达不够、形式化程度低等缺陷。将本体与概念代数结合,提出一种基于概念代数的本体表示方法,其恰好符合领域专家构建本体的意识活动,可以更好地表达和处理知识。概念代数是一种抽象的数学结构,形式化程度较高,并且其概念之间的认知关系更便于进行知识推理。利用概念代数将本体表示为可视化的概念网形式,进而利用概念代数的运算实现概念之间的合并及关联,提出一种基于概念代数的本体合并方法,是对概念代数应用到本体的一种尝试,为本体的处理提供了一个新的视角。     

模糊语义下知识系统的结构及信息传播的研究

文中提出模糊概念空间及规则空间,作为对知识系统进行形式化表示的统一框架.首先,基于形式概念分析理论以及L-模糊集构造了概念粒,通过对概念粒之间关联关系的研究定义了概念射,进而构造了高层次知识单元"概念粒簇".概念粒簇由不同概念粒聚合而成,作为模糊概念空间中的结构层次.其次,通过定义概念粒之间语义整合的先验规则以及积运算构造了规则空间,阐明了概念粒在规则空间的作用下相互之间进行信息传播的机制.文中的结论为进一步研究模糊语义下知识系统的动态构成及演化机制奠定了理论基础.     

机器翻译系统中概念词典的设计与实现

本文介绍了一个机器翻译系统中所需的知识源之一－－概念词典，其知识表示形式、组织结构、每个知识单元的构成，并给出了一个对词典进行图形浏览和编辑的用户界面。     

产品配置领域本体学习方法研究

针对大多数本体构建工具只支持手工构建,造成本体构建效率极低、工作量大、容易出错、知识的动态及时更新和维护困难等问题,提出一种领域本体自动构建的框架系统,通过对企业已有数据库及相关领域中大量的知识进行本体学习,实现配置领域本体自动（或半自动）构建,给出不同数据源结构中的本体概念抽取、概念间语义关系抽取等关键技术。     

Verifying task-based specifications in conceptual graphs

A conceptual model is a model of real world concepts and application domains as perceived by users and developers. It helps developers investigate and represent the semantics of the problem domain, as well as communicate among themselves and with users. In this paper, we propose the use of task-based specifications in conceptual graphs (TBCG) to construct and verify a conceptual model. Task-based specification methodology is used to serve as the mechanism to structure the knowledge captured in the conceptual model; whereas conceptual graphs are adopted as the formalism to express task-based specifications and to provide a reasoning capability for the purpose of verification. Verifying a conceptual model is performed on model specifications of a task through constraints satisfaction and relaxation techniques, and on process specifications of the task based on operators and rules of inference inherited in conceptual graphs.     

UXDs-driven conceptual design process model for contradiction solving using CAIs

Design is situational, which means the explicit consideration of the state of the environment, the knowledge and experience of the designer, and the interaction between the designer and the environment during designing interact. When computer-aided innovation systems (CAIs) are applied to the design, the environment and the situation are different from the traditional design process and environment. The basic principles of some CAIs available in the world market are directly related to theory of inventive problem solving (TRIZ). Special TRIZ solutions, which have a few inventive principles and the related cases for contradiction problem solving, are medium-solutions to domain problems. The second stage analogy process is used to generate domain solutions and in this process, the TRIZ solutions are used as source designs of analogy-based process. Unexpected discoveries (UXDs) are the key factors to trigger designers to generate new ideas for domain solutions. The type of UXDs for the specific TRIZ solutions is studied and a UXDs-driven contradiction solving for conceptual design is formed. A case study shows the application of the process step by step.     

What does it mean? Students’ procedural and conceptual problem solving in a CSCL environment designed within the field of science education

This article discusses the relationship between procedural and conceptual problem solving in a computer-supported collaborative learning (CSCL) environment designed within the field of science education. The contribution of this article, and our understanding of this phenomenon, is anchored in our socio-cultural interpretation, and that implies distinctive inputs for the design and re-design of these kinds of learning environments. We discuss institutional aspects linked to the school as a curriculum deliverer, as well as to the presentation of the knowledge domain and the construction of the CSCL environment. The data is gathered from a design experiment in a science setting in a secondary school, and video data is used to perform an interaction analysis. More specifically, we follow a group of four secondary school students who solve a biological problem in a computer-based 3D model supported by a website. Our findings are clear in the sense that the procedural types of problem solving tend to dominate the students’ interactions, while conceptual knowledge construction is only present where it is strictly necessary to carry out the problem solving. Based on our analyses, we conclude that this can be explained partly by how the knowledge domain is presented and how the CSCL environment is designed, but that the main reason is linked to the institutional aspects related to the school as curriculum deliverer where its target is to secure that the students actually solve problems that are predefined in the syllabus list. We argue that this affords some particular challenges, linked to making conceptual knowledge constructions in science education explicit in the CSCL environment, and to encouraging the teachers and the school as a curriculum deliverer to give this kind of knowledge construction a prioritised value.     

怎样用物性结构知识解决“网球问题”？

“网球问题”指怎样把racquet(网球拍)、ball(网球)和net(球网)之类具有情境联想关系的词汇概念联系起来、发现它们之间的语义和推理关系。这是一个自然语言处理和相关的语言知识资源建设的世界性难题。该文以求解“网球问题”为目标,对目前比较主流的几种语言词汇和概念知识库系统(包括WordNet、VerbNet、FrameNet、ConceptNet等)进行检讨,指出它们在解决“网球问题”上还都存在一定的局限性,着重分析它们为什么不能解决“网球问题”。进而指出基于生成词库论的名词物性结构知识描写体系可以解决“网球问题”,主张用名词的物性结构知识和相关的句法组合知识来构建一种以名词(实体)为核心的词汇概念网络,以弥补上述几种知识库系统的不足,为自然语言处理提供一种可资参考的词汇概念知识库体系。     

Solving the problem of how medical students solve problems

Although gathering and processing information are essential to medical problem solving, little is known about what strategies students use to gather information or how they use their cognitive skills to solve problems. We have developed computer-based problem-solving exercises in immunology to determine how students gather and process information. Graphic representations of students' search paths through different problems were developed to visualize how organized and focused their knowledge was, how well their organization related to critical concepts in immunology, where serious misconceptions (confusion or erroneous models) occurred, and whether proper knowledge links between conceptual domains existed. With rapid generation and interpretation of information on patterns and difficulties in problem solving, it should become possible to develop a specific and personal approach to each student's educational needs.     

基于协同交互式遗传算法的复杂产品概念设计

针对复杂产品概念设计中的方案求解问题,建立了基于进化思想的求解过程模型,提出了一种新的基于协同进化算法与交互式遗传算法相结合的复杂产品概念设计方法.针对手机概念设计中功能设计的特点提出了变长度编码和两层编码的混合编码方式.实例表明,该方法对多目标、人机交互的复杂产品概念设计方案求解是有效的.     

Knowledge representation in human problem solving: implications for expert system design

The study focuses on the identification of the underlying representational properties of human problem solving and their application to expert systems. In this study the interaction between problem representation (procedural, conceptual, unstructured) and problem type (transformation, arrangement, inducing structure) was observed. The results of this study indicate partly that quantitative and qualitative differences in problem-solving performance can be attributed to the form of knowledge representation employed by the problem solver. It is suggested that modularized expert systems could be designed with different problem-solving modules organized by problem characteristics or type, exploiting the representational differences identified in this study.     

A smart conflict resolution model using multi-layer knowledge graph for conceptual design

Reducing the impact of conflicts on requirement-function-structure mapping in the early stage of product design is an important measure to achieve conceptual innovation, which relies on accurate reasoning of multi-domain knowledge. As product requirements become more personalized and diverse, traditional discrete knowledge organization and reasoning methods are difficult to adapt to the challenges of continuity and precision in conceptual solution. Knowledge graphs with complex networks have obvious advantages in association detection, knowledge visualization, and explainable reasoning of implicit knowledge, which offer innovative opportunities for conflict resolution in conceptual design. Therefore, a smart conflict resolution model using a multi-layer Knowledge Graph for Conceptual Design(mKGCD) is proposed in this study. A knowledge expression form of FBS-oriented design patent vocabulary is proposed, which is used for knowledge entity recognition and relation extraction based on natural language processing. A label mapping method based on inventive principles is used for patent classification and a four-layer semantic network for conflict resolution is constructed. Through semantic distance calculation, the designer's requirements for function/behavior/structure are smart deployed to obtain appropriate knowledge. A case study of the conceptual design of a collapsible installation and handling equipment demonstrates the feasibility of the proposed approach. The proposed method can not only meet the functional solution and innovation in the context of different design requirements, but also effectively improve the design efficiency in the iterative design process by means of multiple meanings of one graph.     

Conceptual modeling of causal map: Object oriented causal map

This study has been started from question “Is there a methodology that can make causal map comprised of causality as a database by using conceptual modeling method?” In this research, causal map is proposed to represent causal relation by using conceptual modeling method. Therefore, we formalize causality as a cognitive rule to allow us to control changes in the decision making environment. Such causality is embedded in the real world (application domain). And, user (decision maker) use to represent set of causality which decision-makers have retrieved from the set of knowledge or experiences in application domain. Such set of causality that decision-makers possess in their know–how and short (long) term memory are usually formalized by causal map. It is verified for users whether this causal map is helpful in solving their problems. By extending the basis of conceptual modeling theory (ontology theory, classification theory, decomposition theory, and semantic network theory), we introduce a concept of causal entity diagram and address why causal map is needed to analyze a specific domain knowledge for given decision problem solving. Finally, object oriented causal map (O2CM) were employed to verify usefulness of causal map for user (decision maker) in this study.     

面向属性的归纳与概念聚类

面向属性的归纳是新近提出的一种广泛用于数据库中知识发现的方法，文章指出这种方法与一种机器学习方法－概念聚类之间的紧密联系，并描述如何使用一个概念聚类算法进行面向属性的归纳。