An Iterative Approach to Synthesize Data Transformation Programs
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 1726-1731.
Abstract
Programming-by-Example approaches allow users to transform data by simply entering the target data. However, current methods do not scale well to complicated examples, where there are many examples or the examples are long.In this paper, we present an approach that exploits the fact that users iteratively provide examples.It reuses the previous subprograms to improve the efficiency in generating new programs.We evaluated the approach with a variety of transformation scenarios.The results show that the approach significantly reduces the time used to generate the transformation programs, especially in complicated scenarios.
@inproceedings{ijcai2015p246,
title = {An Iterative Approach to Synthesize Data Transformation Programs},
author = {Wu, Bo and Knoblock, Craig A.},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {1726--1731},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/246},
}
TY - CPAPER TI - An Iterative Approach to Synthesize Data Transformation Programs AU - Wu, Bo AU - Knoblock, Craig A. T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 1726 EP - 1731 UR - https://ijcai.org/proceedings/2015/246 ER -Copied
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