Abstract not found

The knowledge to be acquired for the development of knowledge based systems is often distributed across a group of experts rather than available for elicitation from a single expert. Group elicitation presents major problems because experts can disagree on the use of concepts and vocabulary, and this disagreement may be tacit causing confusion. This paper describes a computer-supported methodology for knowledge acquisition from groups in which the conceptual frameworks of different experts are compared in a way that makes such disagreements overt and readily identifiable.

The knowledge acquisition bottleneck impeding the development of expert systems is being alleviated by the development of computer-based knowledge acquisition tools. These work directly with experts to elicit knowledge, and structure it appropriately to operate as a decision support tool within an expert system. However, the elicitation of expert knowledge and its effective transfer to a useful knowledge-based system is complex and involves a diversity of activities. This paper illustrates the complete development of a decision support system using knowledge acquisition tools. The example is simple enough to be completely analyzed but exhibits enough real-world characteristics to give significant insights into the processes and problems of knowledge engineering. 1 Introduction Knowledge acquisition for expert system development has come to be termed knowledge engineering, following Feigenbaum's (1980) use of the term to describe the reduction of a large body of knowledge to a precise...

There is currently a division in knowledge acquisition research and practice between techniques for the transfer of existing knowledge from human experts and those for the creation of new expertise through machine learning. This paper reports studies of the spectrum of trade-offs between these two extremes, measuring the amount of data required to attain knowledge through empirical induction given different forms and levels of expertise. This gives a principled economic evaluation of knowledge which can be used to guide knowledge acquisition theory and practice.

Knowledge acquisition research supports the generation of knowledge-based systems through the development of principles, techniques, methodologies and tools. What differentiates knowledgebased system development from conventional system development is the emphasis on in-depth understanding and formalization of the relations between the conceptual structures underlying expert performance and the computational structures capable of emulating that performance. Personal construct psychology is a theory of individual and group psychological and social processes that has been used extensively in knowledge acquisition research to model the cognitive processes of human experts. The psychology takes a constructivist position appropriate to the modeling of human knowledge processes but develops this through the characterization of human conceptual structures in axiomatic terms that translate directly to computational form. In particular, there is a close correspondence between the intensional lo...

Widespread access to the Internet has led to the formation of geographically dispersed scientific communities collaborating through the network. The tools supporting such collaboration currently are based primarily on electronic mail through mailing list servers, and access to archives of research reports through ftp, gopher and world wide web. However, electronic communication can support the knowledge processes of scientific communities more directly through overtly represented knowledge structures. This paper describes some experiments in the use of knowledge acquisition (KA) and representation (KR) tools to define and analyze major policy and technical issues in an international research community responsible for one of the test cases in the Intelligent Manufacturing Systems (IMS) research program. It is concluded that distributed knowledge support systems in routine use by world-class scientific communities collaborating through the Internet will provide a major impetus to artific...

One problem of eliciting knowledge from several experts is that experts may share only parts of their terminologies and conceptual systems. Experts may use the same term for different concepts, use different terms for the same concept, use the same term for the same concept, or use different terms and have different concepts. Moreover, clients who use an expert system have even less likelihood of sharing terms and concepts with the experts who produced it. This paper outlines a methodology for eliciting and recognizing such individual differences. It can be used to focus discussion between experts on those differences between them which require resolution, enabling them to classify them in terms of differing terminologies, levels of abstraction, disagreements, and so on. The methodology promotes the full exploration of the conceptual framework of a domain of expertise by encouraging experts to operate in a "brain-storming" mode as a group, using differing viewpoints to develop a rich f...

Object-oriented class libraries offer the potential for individual researchers to manage the large bodies of code generated in the experimental development of complex interactive systems. This article analyzes the structure of such a class library that supports the rapid prototyping of a wide range of systems including collaborative networking, shared documents, hypermedia, machine learning, knowledge acquisition and knowledge representation, and various combinations of these technologies. The overall systems architecture is presented in terms of a heterogeneous collection of systems providing a wide range of application functionalities. Examples are given of group writing, multimedia and knowledge-based systems which are based on combining these functionalities. The detailed design issues of the knowledge representation server component of the system are analyzed in terms of requirements, current state-of-the-art, and the underlying theoretical principles that lead to an effective obj...

An architecture for knowledge acquisition systems is proposed based upon the integration of existing methodologies, techniques and tools developed within the knowledge acquisition, machine learning, expert systems, hypermedia and knowledge representation research communities. Existing tools are analyzed within a common framework to show that their integration can be achieved in a natural and principled fashion. A detailed architecture for integrated knowledge acquisition systems is proposed that also derives from parallel cognitive and theoretical studies. 1 INTRODUCTION The past decade has seen an explosion in research on, and application of, knowledge acquisition methodologies, techniques and tools (Marcus, 1988; Boose & Gaines, 1988, 1990; Gaines & Boose, 1988; Boose, 1989). The knowledge acquisition community world-wide has grown in numbers and scope of projects. There are significant international collaborative developments involving the sharing of ideas and software. The problem ...

: The development of knowledge-based systems involves the management of a diversity of knowledge sources, computing resources and system users, often geographically distributed. The knowledge acquisition, modeling and representation communities have developed a wide range of tools relevant to the development and management of large-scale knowledge-based systems, but the majority of these tools run on individual workstations and use specialist data formats making system integration and knowledge interchange very problematic. However, widespread access to the Internet has led to a new era of distributed client-server computing. In particular, the introduction of support for forms on World Wide Web in late 1993 has provided an easily programmable, cross-platform graphic user interface that has become widely used in innovative interactive systems. This article reports on the development of open architecture knowledge management tools operating through the web to support knowledge acquisiti...