Knowledge Management for the Applied Sciences

Artificial Intelligence in Knowledge Management

Volume

Papers from the 1997 AAAI Spring Symposium

Contents

Expert systems are usually built from knowledge elicited from domain experts. However, knowledge in applied science domains is grounded in published sources like research reports, text books, articles and so on. This corpus of knowledge is typically inconsistent, dated, dispersed, etc. The project described in this paper aims to construct a putative Knowledge Management System. The core of the system is a knowledge server which represents each publication and expert as a separate knowledge base, and a meta-knowledge base to allow different kinds of access to the server. Different client systems can be connected to the knowledge server to meet different user needs such as forecasting, advice, explanation, education, and training. The server can also be a resource lbr researchers and research managers, by allowing hypothesis testing and review of the literature. Knowledge re-engineering is not necessary, as the system simply embodies what is in the domain. The test domain is viticulture, the work being supported by Australia’s Cooperative Research Center for Viticulture.