Learning Transformation Rules by Examples

Authors

  • Bo Wu University of Southern California
  • Pedro Szekely University of Southern California
  • Craig Knoblock University of Southern California

DOI:

https://doi.org/10.1609/aaai.v26i1.8409

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.

Downloads

Published

2021-09-20

How to Cite

Wu, B., Szekely, P., & Knoblock, C. (2021). Learning Transformation Rules by Examples. Proceedings of the AAAI Conference on Artificial Intelligence, 26(1), 2459-2460. https://doi.org/10.1609/aaai.v26i1.8409