Knowledge Engineering
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Enhancing the Knowledge Engineering Process
In 1983, the Commission of the European Communities launched an ambitious 10 year programme in information technology called ESPRIT: European Strategic Programme for Research and Development in Information Technology. The papers in this volume focus on the contributions of the second phase of the programme, ESPRIT II, to the area of knowledge engineering, and more specifically, on the trend towards more disciplined knowledge engineering methodologies. An attempt has been made to establish a coherent volume that will act as a lasting reference source for experts in the field. This has lead to a focus on a small number of projects and topics. Further, contributions have been sourced primarily from those that have established a significant advance in respect of the international state of the art, without losing sight of practical realisability and industrial acceptance. The book captures work centering around the concept of knowledge-level modelling and its use in structuring the complete life-cycle, validating expert systems, acquiring knowledge, enhancing capabilities and achieving genericity and re-use. It shows the high quality and the advanced nature of the research currently being undertaken and indicates that important innovations of extreme relevance to the industry have been achieved. However, further research and advanced development clearly continues to be needed because the European information technology has far from reached the level of competitiveness required to acquire a greater international market share. It is hoped this publication will play an important role in this movement forwards.
Knowledge Engineering
Author: Ela Kumar
language: en
Publisher: I K International Pvt Ltd
Release Date: 2018-09-29
The universe is full of different kinds of knowledge like tangible, intangible, conceptual, static, dynamic and many more. Knowledge Engineering is an advancement of Artificial Intelligence (AI). The present book describes various concepts of artificial intelligence, and other technical aspects of Knowledge Engineering and Computer Science. Knowledge representation is a key aspect of problem formulation from AI viewpoint. In the light of importance of knowledge representation and its analysis, it has emerged as a full-fledged engineering discipline. The book focuses on the concepts and issues of Knowledge Engineering that have impact on business management strategies, productivity, and the key elements of any business and its people. It also discusses, the skills required from the persons working in this area.
Knowledge Engineering
Author: John Debenham
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
This monograph describes a methodology for the design of knowledge-based systems. A knowledge-based system contains knowledge as well as information and data. The information and data in such a system can be modelled and imple mented as a database. The knowledge in such a system can be implemented either in a programming language or in an expert systems shell. This methodology has two distinguishing features. First, it is "unified". A unified methodology repre sents the data, information and knowledge in a homogeneous manner, as well as the relationships between them. Second, the methodology builds a maintenance mechanism into the design. In knowledge engineering terms, the representation used by this methodology to model knowledge bases applies equally to databases. In database terms, the representation used by this methodology to model databases applies equally to the database rules. The unified methodology unifies the design of the "knowledge base compo nent" and the "database component". "Unification" is achieved in five senses.