Learning Transformation Rules by Examples
Abstract
This paper presents an abstract for a general data transformation approach. Using programming by demonstration technique, we learn the transformation rules through user given examples. These transformation rules are automatically generated from a predefined grammar. Due to the grammar space is huge, we propose a grammar space reduction method to reduce the search space and a sketch of search algorithm is adopted to identify the rules that are consistent with the examples. The final experimental results show our approach achieves promising results on different transformation scenarios.
Cite
Text
Wu et al. "Learning Transformation Rules by Examples." AAAI Conference on Artificial Intelligence, 2012. doi:10.1609/AAAI.V26I1.8409Markdown
[Wu et al. "Learning Transformation Rules by Examples." AAAI Conference on Artificial Intelligence, 2012.](https://mlanthology.org/aaai/2012/wu2012aaai-learning/) doi:10.1609/AAAI.V26I1.8409BibTeX
@inproceedings{wu2012aaai-learning,
title = {{Learning Transformation Rules by Examples}},
author = {Wu, Bo and Szekely, Pedro A. and Knoblock, Craig A.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2012},
pages = {2459-2460},
doi = {10.1609/AAAI.V26I1.8409},
url = {https://mlanthology.org/aaai/2012/wu2012aaai-learning/}
}