For successful application of knowledge-based systems, “knowledge transfer” (KT) should be receiving more attention. Knowledge transfer is defined as a flow of knowledge from knowledge suppliers through knowledge-based systems to users. Insufficient state-of-the-application of knowledge-based systems in Japan and its near future directions are analysed in terms of KT. Some example tasks for improving KT are reported. These tasks were experienced by the author in the course of 10 years of research and development on knowledge-based systems for project management.

A technology transfer programme, where people from industry have been educated and trained in knowledge engineering on a project basis, has been in operation since 1984 in the Computer and Information Science Department at Linköping University. This review presents the background for the programme, its organization, examples of training projects, educational activities and plans for the future development.

The University of Edinburgh established the Artificial Institute (AIAI) in 1984 with the objective of transferring the technologies of artificial intelligence from the academic research environment to the practical worlds of commerce, government and industry.

This article outlines the basic corporate engineering process that leads to the commercialization of a knowledge engineering concept, or software process. The development of a commercial product and enterprise from a technology-driven research effort or idea is quite similar to the process of continual refinement and hard work demanded by the scientific method, so the fundamentals of corporate and product development should not appear foreign to academics or those involved in corporate research. Knowledge engineering and related disciplines are on the verge of significant commercial product development efforts. The process of commercialization of ideas, particularly those derived from academic and research environments may not be intuitively obvious to the KE professional. The author outlines the general process of commercializing KE products and describes the three primary functional activities required to undertake a successful technology-driven commercial enterprise—market and customer definition, the development of the product prototype and corporate infrastructure, and capitalization.

As recently as a year ago, trade journal articles that discussed expert systems often carried a great deal of hyperbole and inflated claims. Many otherwise sophisticated technologists put expert-system techniques in the same category with such far-off ideas as orbiting missile defense systems and thinking machines.

Knowledge-based System (KBS) technologies have been applied to a variety of knowledge-related tasks with varying degrees of success. Differentiating among classes of knowledge-related tasks, based on the amounts of problem-solving knowledge and case-specific data involved, can provide valuable insight into why this occurs. Based on this comparison, four classes of problems are described. One class, of data-intensive tasks, includes problem types that are difficult or impossible for humans to perform, yet may be solved in a cost-effective manner using currently accessible KBS technology. The characteristic features of problems in this class are given, together with an example of a successfully fielded knowledge-based system that solves a problem from this class.

The main purpose of this survey was to update a survey report prepared for the UK Alvey Directorate during 1984. The update was focused on business, and had to be qualitative because the increased confidentiality associated with the majority of projects precluded a quantitative analysis, and is confined to a synthesis of the impressions we have obtained. The survey was not intended to be representative. On the contrary, organizations were identified as being amongst those most likely to provide interesting application experience. This led to an arbitrary selection. For example, all banks were excluded because it was felt they were not yet ready to talk of their experiences. The companies approached consisted of five organizations visited in 1983, five further user companies and five service companies (e.g. consultants and software houses).

This paper gives the personal view of a Japanese knowledge engineer, concerning the present status of the evolution of knowledge engineering in Japan, especially its applications in the business field, user evaluation and acceptance, problems, and future prospects.

There is a growing awareness of the potential of expert systems in the accounting profession, although the number of applications is limited. This paper assesses whether the profession is dragging its heels, or whether it is being wisely cautious.

Solving a legal problem is a complex business. First, the lawyer—or whoever is doing the solving—has to assemble and marshall the facts of his case in as orderly a fashion as his knowledge of the relevant law will allow. Secondly, he must confront the range of pertinent legal sources and decompose these into manageable and applicable units. Thirdly, he will subsume the particular facts of his case under the more general terms of his decomposed units. And, finally, he draws inferences about the applicable legal provisions and their impact on the facts. Of course, assembly, decomposition, subsumption and inference may not occur in linear progression. What is more, problems can cccur at each stage and interim evaluations and judgments must be made.