Skip to main content
SpringerLink
Log in
Book cover

Knowledge Acquisition: Selected Research and Commentary

A Special Issue of Machine Learning on Knowledge Acquisition

  • Book
  • © 1990

Overview

Editors:
  1. Sandra Marcus

    1. Boeing Computer Services, Seattle, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

  1. Front Matter

    Pages i-iii
    Download chapter PDF

  2. Introduction: A Sampler in Knowledge Acquisition for the Machine Learning Community

    • Sandra Marcus
    Pages 1-3

  3. Can Machine Learning Offer Anything to Expert Systems?

    • Bruce G. Buchanan
    Pages 5-8

  4. When Will Machines Learn?

    • Douglas B. Lenat
    Pages 9-11

  5. Supporting Start-to-Finish Development of Knowledge Bases

    • Ray Bareiss, Bruce W. Porter, Kenneth S. Murray
    Pages 13-37

  6. The Knowledge Level Reinterpreted: Modeling How Systems Interact

    • William J. Clancey
    Pages 39-45

  7. Automated Knowledge Acquisition for Strategic Knowledge

    • Thomas R. Gruber
    Pages 47-90

  8. The World Would Be a Better Place if Non-Programmers Could Program

    • John McDermott
    Pages 91-92

  9. Task-Structures, Knowledge Acquisition and Learning

    • B. Chandrasekaran
    Pages 93-99

  10. Automated Support for Building and Extending Expert Models

    • Mark A. Musen
    Pages 101-129

  11. Knowledge Acquisition for Knowledge-Based Systems: Notes on the State-of-the-Art

    • John H. Boose, Brian R. Gaines
    Pages 131-148

  12. Back Matter

    Pages 149-152
    Download chapter PDF
Back to top

Keywords

About this book

What follows is a sampler of work in knowledge acquisition. It comprises three technical papers and six guest editorials. The technical papers give an in-depth look at some of the important issues and current approaches in knowledge acquisition. The editorials were pro­ duced by authors who were basically invited to sound off. I've tried to group and order the contributions somewhat coherently. The following annotations emphasize the connections among the separate pieces. Buchanan's editorial starts on the theme of "Can machine learning offer anything to expert systems?" He emphasizes the practical goals of knowledge acquisition and the challenge of aiming for them. Lenat's editorial briefly describes experience in the development of CYC that straddles both fields. He outlines a two-phase development that relies on an engineering approach early on and aims for a crossover to more automated techniques as the size of the knowledge base increases. Bareiss, Porter, and Murray give the first technical paper. It comes from a laboratory of machine learning researchers who have taken an interest in supporting the development of knowledge bases, with an emphasis on how development changes with the growth of the knowledge base. The paper describes two systems. The first, Protos, adjusts the training it expects and the assistance it provides as its knowledge grows. The second, KI, is a system that helps integrate knowledge into an already very large knowledge base.

Editors and Affiliations

  • Boeing Computer Services, Seattle, USA

    Sandra Marcus

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation