Automatic Rule Acquisition for Spelling Correction
Abstract
This paper describes a new approach to automatically learning linguistic knowledge for spelling correction. A major feature of this approach is the fact that the acquired knowledge is captured in a small set of easily understood rules, as opposed to a large set of opaque features and weights. A perspicuous representation is advantageous in order to best exploit human intuition to understand and improve upon the acquired knowledge of the system.
Cite
Text
Mangu and Brill. "Automatic Rule Acquisition for Spelling Correction." International Conference on Machine Learning, 1997.Markdown
[Mangu and Brill. "Automatic Rule Acquisition for Spelling Correction." International Conference on Machine Learning, 1997.](https://mlanthology.org/icml/1997/mangu1997icml-automatic/)BibTeX
@inproceedings{mangu1997icml-automatic,
title = {{Automatic Rule Acquisition for Spelling Correction}},
author = {Mangu, Lidia and Brill, Eric},
booktitle = {International Conference on Machine Learning},
year = {1997},
pages = {187-194},
url = {https://mlanthology.org/icml/1997/mangu1997icml-automatic/}
}