A Case Study of Knowledge Representation in UC
Abstract
The knowledge representation used in UC provides a flexible framework suitable for a large variety of natural language processing tasks including parsing, inference, planning, goal analysis, and generation. Although many of the knowledge structures are specific to the UNIX Consultant domain, a common design goal is the use of associative processing. By providing direct links between related knowledge structures, inference and other processing can be done very efficiently. Access to representations in UC is by hash indexing which simulates a real associative memory.
Cite
Text
Chin. "A Case Study of Knowledge Representation in UC." International Joint Conference on Artificial Intelligence, 1983.Markdown
[Chin. "A Case Study of Knowledge Representation in UC." International Joint Conference on Artificial Intelligence, 1983.](https://mlanthology.org/ijcai/1983/chin1983ijcai-case/)BibTeX
@inproceedings{chin1983ijcai-case,
title = {{A Case Study of Knowledge Representation in UC}},
author = {Chin, David N.},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1983},
pages = {388-390},
url = {https://mlanthology.org/ijcai/1983/chin1983ijcai-case/}
}