Knowledge Acquisition in Practice [electronic resource] : A Step-by-step Guide / by N. R. Milton.Material type: TextLanguage: English Series: Decision Engineering: Publisher: London : Springer London, 2007Description: XII, 176 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781846288616Subject(s): Engineering | Engineering economy | Management information systems | Engineering | Engineering Economics, Organization, Logistics, Marketing | Business Information Systems | Systems and Information Theory in EngineeringAdditional physical formats: Printed edition:: No titleDDC classification: 658.5 LOC classification: TA177.4-185Online resources: Click here to access online
Overview of the Step-by-step Procedure -- Start, Scope and Plan the Project -- Initial Capture and Modelling -- Detailed Capture and Modelling -- Share the Stored Knowledge -- Implementation Issues.
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 in Practice 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 in Practice 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.