Supporting Start-to-Finish Development of Knowledge Bases

Abstract

Developing knowledge bases using knowledge-acquisition tools is difficult because each stage of development requires performing a distinct knowledge-acquisition task. This paper describes these different tasks and surveys current tools that perform them. It also addresses two issues confronting tools for start-to-finish development of knowledge bases. The first issue is how to support multiple stages of development. This paper describes Protos, a knowledge-acquisition tool that adjusts the training it expects and assistance it provides as its knowledge grows. The second issue is how to integrate new information into a large knowledge base. This issue is addressed in the description of a second tool, KI, that evaluates new information to determine its consequences for existing knowledge.

Cite

Text

Bareiss et al. "Supporting Start-to-Finish Development of Knowledge Bases." Machine Learning, 1989. doi:10.1007/BF00130714

Markdown

[Bareiss et al. "Supporting Start-to-Finish Development of Knowledge Bases." Machine Learning, 1989.](https://mlanthology.org/mlj/1989/bareiss1989mlj-supporting/) doi:10.1007/BF00130714

BibTeX

@article{bareiss1989mlj-supporting,
  title     = {{Supporting Start-to-Finish Development of Knowledge Bases}},
  author    = {Bareiss, Ray and Porter, Bruce W. and Murray, Kenneth S.},
  journal   = {Machine Learning},
  year      = {1989},
  pages     = {259-283},
  doi       = {10.1007/BF00130714},
  volume    = {4},
  url       = {https://mlanthology.org/mlj/1989/bareiss1989mlj-supporting/}
}