Only book to present a step-by-step guide that walks the reader through a knowledge acquisition project, presenting a methodology that can be used for any area of expertise and any type of expert
Will enable the reader to identify, capture, store and disseminate expertise that is vital to an organisation in an efficient and effective manner that minimises the resources required whilst maximising the use and re-use of the captured knowledge
Includes supplementary material: sn.pub/extras
Part of the book series: Decision Engineering (DECENGIN)
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Table of contents (7 chapters)
About this book
Recent years have seen an upsurge of interest in knowledge. Leading organisations now recognise the importance of identifying what they know, sharing what they know and using what they know for maximum benefit. Many organisations employ knowledge engineers to capture knowledge from experts using the principles and techniques of knowledge engineering. The emphasis is on a structured approach built on a sound understanding of the psychology of expertise and making use of knowledge modelling methods and the latest web technologies.
Knowledge Acquisition Projects is the first book to provide a detailed step-by-step guide to the methods and practical aspects of acquiring, modelling, storing and sharing knowledge. The reader is led through 47 steps from the inception of a project to its successful conclusion. Each step is described in terms of the reasons for the step, the required resources, the activities to be undertaken, and the solutions to common problems. In addition, each step has a checklist which lists the key items that should be achieved during the step.
Knowledge Acquisition Projects will be of value to knowledge engineers, knowledge workers, knowledge officers and ontological engineers. The book will also be of interest to students and researchers of AI, computer science and business studies.
- Knowledge Acquisition
- Knowledge Capture
- Knowledge Management
- Knowledge Modelling
- computer science
- knowledge engineering
- Engineering Economics
From the reviews:
"Building on Nigel Shadbolt’s pioneering work in the field of knowledge acquisition, Milton, prominent artificial intelligence researcher, here provides a clear guide for knowledge acquisition projects. … Overall, this comprehensive work approaches knowledge bases holistically, by exploring both the process of creating knowledge bases and the strengths and weaknesses of competing knowledge base structures. Glossary, index, appendixes, bibliography. A highly technical work appropriate for academic libraries. Summing Up: Highly recommended. Upper-division undergraduates through professionals." (K. J. Whitehair, CHOICE, Vol. 45 (5), January, 2008)
Authors and Affiliations
N. R. Milton
Tacit Connexions, UK
N. R. Milton
About the author
Dr Nick Milton has worked in the area of knowledge engineering and knowledge acquisition for over 10 years, first as a researcher at the University of Nottingham, then as a consultant Knowledge Engineer, and now as Chief Knowledge Architect at Epistemics Ltd. As a researcher, he worked on the development of techniques taken from AI (for capturing expert knowledge) for their use in Knowledge Management. As a consultant Knowledge Engineer he has worked on multiple knowledge acquisition projects and helped develop and implement methodologies for a number of large organizations. He has provided training and support to many hundreds of knowledge engineers (e.g. in Airbus, Rolls-Royce and BAE Systems). He is an expert in the PCPACK software tool and part of its development team. A major thrust of his work has been to maximize the benefits of knowledge engineering to a company while also enabling novice knowledge engineers to learn and apply the approach.
Book Title: Knowledge Acquisition in Practice
Book Subtitle: A Step-by-step Guide
Authors: N. R. Milton
Series Title: Decision Engineering
Publisher: Springer London
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag London 2007
Hardcover ISBN: 978-1-84628-860-9Published: 20 June 2007
Softcover ISBN: 978-1-84996-661-0Published: 10 November 2010
eBook ISBN: 978-1-84628-861-6Published: 01 May 2007
Series ISSN: 1619-5736
Series E-ISSN: 2197-6589
Edition Number: 1
Number of Pages: XII, 176
Topics: Artificial Intelligence, Industrial Management, IT in Business, Applied Dynamical Systems