Knowledge Acquisition in Practice


Book Description

This is the first book to provide a 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 conclusion. Each is described in terms of reasons, required resources, activities, and solutions to common problems. In addition, each step has a checklist which tracks the key items that should be achieved.




Acquisition and Understanding of Process Knowledge Using Problem Solving Methods


Book Description

The development of knowledge-based systems is usually approached through the combined skills of knowledge engineers (KEs) and subject matter experts (SMEs). One of the most critical steps in this activity aims at transferring knowledge from SMEs to formal, machine-readable representations, which allow systems to reason with such knowledge. However, this is a costly and error prone task. Alleviating the knowledge acquisition bottleneck requires enabling SMEs with the means to produce the desired knowledge representations without the help of KEs. This is especially difficult in the case of complex knowledge types, like processes. The analysis of different application domains uncovers that process knowledge is one of the most frequent knowledge types, whose complexity requires specific means to enable SMEs to represent processes in a computational form. Additionally, such complexity and the increasingly large amount of data that process executions generate in knowledge-intensive domains, like Biology or Astronomy, requires analytical means with high abstraction capabilities to support SMEs in the analysis of such processes. This book presents methods and tools that enable SMEs to acquire process knowledge from the domains, formally represent such knowledge, reason about it, and understand process executions by analyzing their provenance. We describe the utilization of Problem Solving Methods as the main knowledge artifacts for process acquisition and analysis in two innovative ways. First, as formalizations of the reasoning strategies needed for processes and, second, as high-level, domain-independent, and reusable abstractions of process knowledge to provide SMEs with interpretations of process executions.




Knowledge Acquisition, Modeling and Management


Book Description

This book constitutes the refereed proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management, EKAW '99, held at Dagstuhl Castle, Germany in May 1999. The volume presents 16 revised full papers and 15 revised short papers were carefully reviewed and selected form a high number of submissions. Also included are two invited papers. The papers address issues of knowledge acquisition (i.e., the process of extracting, creating, structuring knowledge, etc.), of knowledge-level modeling for knowledge-based systems, and of applying and redefining this work in a knowledge management and knowledge engineering context.




New Approaches to Knowledge Acquisition


Book Description

It is well recognized that knowledge acquisition is the critical bottleneck of knowledge engineering. This book presents three major approaches of current research in this field, namely the psychological approach, the artificial intelligence approach and the software engineering approach. Special attention is paid to the most recent advances in knowledge acquisition research, especially those made by Chinese computer scientists. A special chapter is devoted to its applications in other fields, e.g. language analysis, software engineering, computer-aided instruction, etc., which were done in China.




A Future for Knowledge Acquisition


Book Description

In the last few years rapid advances have been made in reproductive medicine, making it necessary for those involved to regularly update their knowledge. The purpose of this book is to describe the state of the art in this field, making it possible for the reader to gain an orientation among all the diagnostic and therapeutic potentials of modern reproductive medicine in order to advise patients fully. Chapters from the fields of gynecology, and reproductive medicine in a specific sense provide knowledge about these subjects. Authors of international standing have contributed chapters on their specialties. These chapters together form a book describing the state of the art in the diagnosis and therapy of sterility in gynecology and andrology.




Knowledge Acquisition for Expert Systems


Book Description

Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech nique are summarized at the end of each chapter with some suggested guidelines for its use. We hope that this book will not only serve as a practical handbook for expert system builders, but also be of interest to AI and cognitive scientists who are seeking to develop a theory of knowledge acquisition for expert systems.




Current Trends in Knowledge Acquisition


Book Description

Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.




The Acquisition of Knowledge and Skills for Taskwork and Teamwork to Control Complex Technical Systems


Book Description

This book provides the first comprehensive literature review on the acquisition and retention of complex skills in High Reliability Organizations. Based on this review, it introduces a theoretical model of how skill and knowledge acquisition for complex tasks is accomplished and shows how this model can be used to derive training methods and instructional techniques. Successful acquisition and retention of complex technical skills within High Reliability Organizations requires a full understanding of the learning process, knowledge structure, and skill requirements associated with the effective operation and management of technology. For researchers and for organizations, the understanding of these processes is vital for designing training programs as well as for reducing errors with severe consequences for human lives and the environment. Until now, only theoretical fragments exist on this topic, and only a very limited number of publications actually address complex tasks in vocational/occupational settings. “The Acquisition of Knowledge and Skills for Task Work and Teamwork to Control Complex Technical Systems ” uses its literature overview and theoretical model to formulate training principles, that can be used to develop training experiments for further empirical investigations as well as training methods for applied organizational contexts.




The Cognitive Psychology of Knowledge


Book Description

The present book is a result of a seven-year (1986-1992) national research program in cognitive science in Germany, presumably the first large scale cognitive science program there. Anchored in psychology, and therefore christened Wissenpsychologie (psychology of knowledge), it has found interdisciplinary resonance, especially in artificial intelligence and education. The research program brought together cognitive scientists from over twenty German universities and more than thirty single projects were funded. The program was initiated by Heinz Mandl and Hans Spada, the main goals of which were to investigate the acquisition of knowledge, the access to knowledge, and the modification and application of knowledge from a psychological perspective. Emphasis was placed on formalisms of knowledge representation and on the processes involved. In many of the projects this was combined with computer simulations. A final but equally important goal was the development of experimental paradigms and methods for data analysis that are especially suited to investigate knowledge based processes.The research program has had a major impact on cognitive psychology in Germany. Research groups were established at many universities and research equipment was provided. It also inspired a considerable number of young scientists to carry out cognitive research, employ modeling techniques from artificial intelligence for psychological theorizing, and construct intelligent tutoring systems for education. Close contacts with cognitive scientists in the U.S. have helped to firmly integrate the program with international research endeavours. Each year, one or two workshops were held. The present volume is the result of the final workshop which was held in September 1992. Selected results from seventeen projects are presented in this book. The volume is enriched by three guest scholars who agreed to participate in the final workshop and to comment on the chapters of the book.




Knowledge Acquisition for Expert Systems


Book Description

Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech nique are summarized at the end of each chapter with some suggested guidelines for its use. We hope that this book will not only serve as a practical handbook for expert system builders, but also be of interest to AI and cognitive scientists who are seeking to develop a theory of knowledge acquisition for expert systems.