Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types

Construction of Neural Network Classification Expert Systems Using Switching Theory Algorithms

A new family of neural network architectures is presented. This family of architectures solves the problem of constructing and training minimal neural network classification expert systems by using switching theory. The primary insight that leads to the use of switching theory is that the problem of minimizing the number of rules and the number of IF statements (antecedents) per rule in a neural network expert system can be recast into the problem of minimizing the number of digital gates and the number of connections between digital gates in a Very Large Scale Integrated (VLSI) circuit. The rules that the neural network generates to perform a task are readily extractable from the network's weights and topology. Analysis and simulations on the Mushroom database illustrate the system's performance

Eliciting Expert Knowledge for Fuzzy Evaluation of Agricultural Production Systems

Public concern nowadays is an important frame of reference for thedevelopment of agricultural production systems. The development ofsuch systems, therefore, involves both society level and productionsystem level. Following Zadeh's principle of incompatibility,information obtained at production system level is interpreted atsociety level in linguistic terms. Fuzzy models promise to be avaluable tool as they link measurable information to linguisticinterpretation using membership functions. The objective of this paperis to outline a procedure which deals with criticism regarding theinherent subjectivity in the construction of membership functions whenusing expert knowledge. The procedure guarantees the selection ofappropriate expert knowledge, and provides a guideline supporting theselection of methods to elicit expert knowledge and constructmembership functions. Also on the basis of the results in anillustrative example, it is concluded that the procedure outlined inthis paper suitably deals with criticism regarding membershipfunctions and, therefore, enables a practical implementation of fuzzyevaluation of agricultural production systems. Current researchimplements the procedure to build a fuzzy model which evaluates eggproduction systems in relation to public concern about the welfare oflaying hens.evaluation;subjectivity;expert knowledge;fuzzy models;knowledge elicitation

Embedding expert systems in semi-formal domains : examining the boundaries of the knowledge base

This thesis examines the use of expert systems in semi-formal domains. The research identifies the main problems with semi-formal domains and proposes and evaluates a number of different solutions to them. The thesis considers the traditional approach to developing expert systems, which sees domains as being formal, and notes that it continuously faces problems that result from informal features of the problem domain. To circumvent these difficulties experience or other subjective qualities are often used but they are not supported by the traditional approach to design. The thesis examines the formal approach and compares it with a semiformal approach to designing expert systems which is heavily influenced by the socio-technical view of information systems. From this basis it examines a number of problems that limit the construction and use of knowledge bases in semi-formal domains. These limitations arise from the nature of the problem being tackled, in particular problems of natural language communication and tacit knowledge and also from the character of computer technology and the role it plays. The thesis explores the possible mismatch between a human user and the machine and models the various types of confusion that arise. The thesis describes a number of practical solutions to overcome the problems identified. These solutions are implemented in an expert system shell (PESYS), developed as part of the research. The resulting solutions, based on non-linear documents and other software tools that open up the reasoning of the system, support users of expert systems in examining the boundaries of the knowledge base to help them avoid and overcome any confusion that has arisen. In this way users are encouraged to use their own skills and experiences in conjunction with an expert system to successfully exploit this technology in semi-formal domains

The generic task toolset: High level languages for the construction of planning and problem solving systems

The current generation of languages for the construction of knowledge-based systems as being at too low a level of abstraction is criticized, and the need for higher level languages for building problem solving systems is advanced. A notion of generic information processing tasks in knowledge-based problem solving is introduced. A toolset which can be used to build expert systems in a way that enhances intelligibility and productivity in knowledge acquistion and system construction is described. The power of these ideas is illustrated by paying special attention to a high level language called DSPL. A description is given of how it was used in the construction of a system called MPA, which assists with planning in the domain of offensive counter air missions

An expert system approach to astronomical data analysis

Expert systems technology has much to offer to the problem of astronomical data analysis, where large data volumes and sophisticated analysis goals have caused a variety of interesting problems to arise. The construction of a prototype expert system whose target domain is CCD image calibration, is reported. The prototype is designed to be extensible to different and more complex problems in a straighforward way, and to be largely independent of the details of the specific data analysis system which executes the plan it generates

The construction of statistical expert systems with applications

PhD ThesisStatistical expert systems have grown more numerous over the last few years. However, the tools which are used in their development are largely modifications of existing methods from other areas. This means that the unique aspects of statistical problems may be omitted in their development. This thesis examines the way that a statistical consultant works, and proposes guidelines and tools for system development based on this. Section I provides a brief introduction to this area. Section II considers the problems faced in establishing the actual problem brought by a client. Two areas of particular interest are establishing the background subject and the facts of a problem. Two methods are proposed to tackle these areas. Also of interest is the way in which a consultant may select a statistical test. Section III introduces a program to elicit the rules used by a consultant. A disk containing the program and the functions used is included with this thesis.Science and Engineering Research Counci

Анализ функциональных возможностей экспертных систем, используемых для диагностики состояния высоковольтного маслонаполненного оборудования

В статье рассмотрены принципы построения и функциональные возможности экспертных систем для диагностики состояния высоковольтного электроэнергетического оборудования. Проанализировано достоинства и недостатки действующих экспертных систем. Предложенные критерии для оценки эффективности разных экспертных систем.In article principles of construction and functionalities of the expert systems used for diagnostics of a condition of the high-voltage electropower equipment are considered. Merits and demerits of working expert systems are analysed. Criteria for an estimation of efficiency of various expert systems are offered