A frame-based knowledge representation model and its mapping to nested relations

The first part of this paper introduces the basic constructs of a frame representation model and gives a formal definition for them. Subsequently the nested relational model (NF²) is described as an extension of the classical relational model to support relation-valued attributes. In the second part of this paper both models are compared with each other and a mapping of frame representation structures to NF² structures is specified. The structural similarities between frames and NF² relations are made clear and it is shown that their main difference is due to the type polymorphism introduced by the concept hierarchy of the frame model. This causes type collisions to occur in the strictly typed NF² model when frames are directly mapped to NF² structures. Two solutions to this problem are suggested and compared. The paper concludes with a reformulation of query operations of the frame model in terms of NF² algebra operations.     

Hierarchical representation of legal knowledge with metaprogramming in logic

We present an application of metaprogramming in logic that, unlike most metaprogramming applications, is not primarily concerned with controlling the execution of logic programs. Metalevel computation is used to define theories from schemata that were either given explicitly or obtained by abstraction from other theories. Our main application is a representation of legal knowledge in a metalogic programming language. We argue that legal knowledge is multilayered and therefore a single level representation language lacks the needed expressiveness. We show that legal rules can be partitioned into primary, secondary, tertiary, quaternary, and higher level rules. Our classification enables us to define a multilevel model of legal knowledge and a one-to-one correspondence with levels of metaprogramming in logic. We show that this framework has a potential for capturing important legal interpretation principles such as analogia legis, lex specialis legi generali derogat, etc. We have a running example from commercial law that utilizes rules up to the tertiary level, emphasizing analogia legis. The example is expressed in a multilevel metalogic programming language that provides a naming convention and employs reflection between levels.     

Approximate knowledge modeling and classification in a frame-based language: The system CAIN

In this article, we present an extension of the frame-based language Objlog+, called CAIN, which allows the homogeneous representation of approximate knowledge (fuzzy, uncertain, and default knowledge) by means of new facets. We developed elements to manage approximate knowledge: fuzzy operators, extension of the inheritance mechanisms, and weighting of structural links. Contrary to other works in the domain, our system is strongly based on a theoretical approach inspired from Zadeh's and Dubois' works. We also defined an original instance classification mechanism, which has the ability to take into account the notions of typicality and similarity as they are presented in the psychological literature. Our model proposes consideration of a particular semantics of default values to estimate the typicality between a class and the instance to classify (ITC). In that way, the possibilities of the typicality representation proposed by frame-based languages are exploited. To find the most appropriate solution we do not systematically choose the most specific class that matches the ITC but we retain the most typical solution. Approximate knowledge is used to make the matching used during the classification process more flexible. Taking into account additional knowledge concerning heuristics and elements of cognitive psychology leads to the enrichment of the classification mechanism. © 2001 John Wiley & Sons, Inc.     

工艺知识管理系统的设计

工艺知识库是CAPP系统的重要组成部分。本文提出一种分类层次模型以组织和管理工艺知识，并据此建立工艺知识库PPKBS。用四种形式表达工艺知识，并以外部和内部两种形式表现。提出了工艺知识的冗余、矛盾和句法结构检查方法。     

Pushing the envelope: challenges in a frame-based representation of human anatomy

One of the main threads in the history of knowledge-representation formalisms is the trade-off between the expressiveness of first-order logic on the one hand and the tractability and ease-of-use of frame-based systems on the other hand. Frame-based systems provide intuitive, cognitively easy-to-understand, and scalable means for modeling a domain. However, when a domain model is particularly complex, frame-based representation may lead to complicated and sometimes awkward solutions. We have encountered such problems when developing the Digital Anatomist Foundational Model, an ontology aimed at representing comprehensively the physical organization of the human body. We show that traditional frame-based techniques such as is-a hierarchies, slots (roles) and role restrictions are not sufficient for a comprehensive model of this domain. The diverse modeling challenges and problems in this project required us to use such knowledge-representation techniques as reified relations, metaclasses and a metaclass hierarchy, different propagation patterns for template and own slots, and so on. We posit that even though the modeling structure imposed by frame-based systems may sometimes lead to complicated solutions, it is still worthwhile to use frame-based representation for very large-scale projects such as this one.     

Concept classifier for knowledge acquisition in frame-based systems

Frame-based systems that employ inheritance networks as a form of knowledge representation have a number of inherent knowledge acquisition problems, one of the most significant being the transfer to the representation system of knowledge itself. The problem of concept classification, and specifically that of determining the location of a new concept in an existing network inheritance hierarchy, is discussed here using an experimental knowledge-base editor, KRE. Tools which support the process of knowledge base construction must allow the user to concentrate on the domain problems, and not on low level, representation system decisions. KRE, written in C, is a knowledge acquisition tool which assists the knowledge engineer by using an interactive acquisition strategy during the process of concept classification. The processes of classification, and its advantages over other knowledge representation systems, are presented.     

Case-based process planning using an object-oriented model representation

This research focuses on the development of a process-planning system. This system utilizes case-based techniques for process selection and sequencing to combine the advantages of the variant and generative approaches to process planning. The case-based process planner utilizes an object-oriented model representation to operate on general three-dimensional prismatic parts, which are represented by a collection of features (e.g. slots, pockets, holes, etc.). Each feature subplan is developed by the case-based planner. Then the feature subplans are combined into the global process plan for the part via a hierarchical plan-merging mechanism. Abstracted feature subplans correspond to cases, which are used in subsequent planning operations to solve new problems. The abstracting and storing of feature subplans as cases is the primary mechanism by which the planner learns from its previous experiences to become more effective and efficient.     

面向工艺设计过程的知识管理的研究

工艺知识有很多种类和表达方法,而本体可以为知识共享和重用提供手段。提出了工艺知识本体的三个层次,明确了与工艺知识有关的概念和术语的层次关系,从而形成工艺知识的整体视野。举例说明了工艺知识中领域概念的提取及其在知识库中的使用,论述了工艺知识查询时本体发挥的作用,从本体建模元语的角度分析,利用知识本体的概念相似度进行语义检索,并结合机床的例子说明其在工艺知识管理中的应用。为了提高知识利用效率,明确了面向工艺设计过程的各种工艺知识需求。最后介绍了基于本体的工艺知识管理系统的框架以及原型系统的开发方法,并进行了初步应用验证。     

ROM: a reliability knowledge representation for collaborative system design

Designing systems that satisfy target reliability is a challenge because of complex assembly structures and logical connections, numerous components and associated failure modes, and multi-disciplinary considerations. To overcome these difficulties and to design reliable systems in a systematic way, we have developed a knowledge representation for system design-for-reliability (SDfR). It is called reliability object model (ROM). ROM includes (1) a new reliability analysis structure, (2) reliability metrics that consider both random failures and wear-out failures, (3) algorithms that allocate, predict, and assess reliability, and (4) rules for reliability-oriented design change recommendations. These capabilities of ROM are demonstrated by prototype SDfR tools and three electronic system case studies. The results show that ROM is an effective unified method for SDfR, providing richer semantics and increasing the chances of developing reliable designs.     

Research on auto-reasoning process planning using a knowledge based semantic net

A process-planning model (PP model) is proposed to convert the geometric features into manufacture machining operations and sequence the machining operations of the part in a feasible and effective order. The process-planning model (PP model) construct a feature framework that makes a mapping from geometric features into machining operations. A semantic net named the Precedence-Relations-Net is established to reflect the precedence relationships among the machining operations. The vectors and the matrixes are employed to construct a mathematical sequencing model. A part is decomposed into several basic geometrical units, namely, U₁, U₂, … , U_N. For each unit U_i, two vectors, named F_i and P_i, represent the features and machining operations of U_i. Finally, a matrix named PP is used to memorize the process plan, and a matrix – PO (performing objects) – represents the object of machining operations.     

Fault diagnosis of a mixing process using deep qualitative knowledge representation of physical behaviour

This paper describes an on-line fault diagnosis system which diagnoses faults in a pilot scale mixing process using on-line measurements. Fault detection and fault diagnosis is performed based on a qualitative model of the mixing process. The qualitative model provides a set of constraints for the system being diagnosed. Once it is violated, a particular fault is detected. Since most of the information used by the diagnosis system comes from on-line measurements, it is important to determine whether sensors are working normally or not before considering failures of other components. Sensor failure is mainly diagnosed from heuristic considerations, while the failures of other components are diagnosed from a procedure of hypothesis generation, qualitative simulation, and comparison. Based on a hypothesis, the behaviour of the system being diagnosed is simulated from its qualitative model and is compared with the actual measurements. Depending upon whether they conflict or not, the hypothesis is denied or retained. A new approach for reducing the ambiguity in qualitative simulation is described. Ambiguity is reduced by taking account of the information on the order of magnitude relations between different physical variables.     

Hierarchical multistrategy genetic algorithm for integrated process planning and scheduling

Journal of Intelligent Manufacturing - To adapt to the flexibility characteristics of modern manufacturing enterprises and the dynamics of manufacturing subsystems, promote collaboration in...     

工艺设计知识库的建造与维护

文中根据工艺设计知识的特点,构造了层次化的知识表达、组织与知识库模型,分析了工艺知识库不一致的表现形式,并给出了相应的一致性验证算法,提出了基于广义决策表的知识库完备性检查方法。     

不确定性工艺知识的模糊粗糙隶属度函数表示方法*

分析了工艺知识不确定性和模糊性的特点,提出了基于模糊粗糙隶属度函数的工艺不确定性知识的表示与应用模型。实现了对各类用数值和符号描述的工艺不确定知识的表示,通过隶属度值代替粗糙集中的实数值作为模糊粗糙集的属性,依照属性的依赖度和属性表的核进行了工艺知识属性的约简,得到了工艺知识规则集,并以LED芯片制造领域的工艺知识表示为实例,验证了该方法的可行性与有效性。     

A new process knowledge representation approach using parameter flow chart

Knowledge in various stages of the product development process has become increasingly important for manufacturing companies to improve their performance, especially for those One-of-a-Kind Production (OKP) companies producing highly customized products. Process knowledge is a very special type of knowledge that controls how products are best manufactured. This knowledge can help OKP companies produce high value-added products with better quality at shorter times and at a competitive cost. Process knowledge is normally hard to capture and manage and is even more difficult to represent. This paper proposes a Parameter Flow Chart (PFC) based new knowledge representation method which efficiently combines parameter information, flow chart technology, and visualization technology. The goal of this research is to provide a user-friendly and effective way of representing process knowledge for OKP companies so they can develop and accumulate their own process knowledge repository. The basic definition and principle of the approach will be introduced first and the software system model then proposed. Two related key issues, the modeling of various chart units used in the PFC approach and dealing with expressions containing various parameters, are discussed in detail. The prototype version of the system has been developed and demonstrated with case studies, which has proven the feasibility of the proposed approach.     

A framework and computer system for knowledge-level acquisition,representation, and reasoning with process knowledge

The development of knowledge-based systems is usually approached through the combined skills of software and knowledge engineers (SEs and KEs, respectively) and of subject matter experts (SMEs). One of the most critical steps in this task aims at transferring knowledge from SMEs’ expertise to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this process is costly and error prone. Alleviating such knowledge acquisition bottleneck requires enabling SMEs with the means to produce the target knowledge representations, minimizing the intervention of KEs. This is especially difficult in the case of complex knowledge types like processes. The analysis of scientific domains like Biology, Chemistry, and Physics uncovers: (i) that process knowledge is the single most frequent type of knowledge occurring in such domains and (ii) specific solutions need to be devised in order to allow SMEs to represent it in a computational form. We present a framework and computer system for the acquisition and representation of process knowledge in scientific domains by SMEs. We propose methods and techniques to enable SMEs to acquire process knowledge from the domains, to formally represent it, and to reason about it. We have developed an abstract process metamodel and a library of problem solving methods (PSMs), which support these tasks, respectively providing the terminology for SME-tailored process diagrams and an abstract formalization of the strategies needed for reasoning about processes. We have implemented this approach as part of the DarkMatter system and formally evaluated it in the context of the intermediate evaluation of Project Halo, an initiative aiming at the creation of question answering systems by SMEs.