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/BF00130714Markdown
[Bareiss et al. "Supporting Start-to-Finish Development of Knowledge Bases." Machine Learning, 1989.](https://mlanthology.org/mlj/1989/bareiss1989mlj-supporting/) doi:10.1007/BF00130714BibTeX
@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/}
}