Query Transformations for Improving the Efficiency of ILP Systems
Abstract
Relatively simple transformations can speed up the execution of queries for data mining considerably. While some ILP systems use such transformations, relatively little is known about them or how they relate to each other. This paper describes a number of such transformations. Not all of them are novel, but there have been no studies comparing their efficacy. The main contributions of the paper are: (a) it clarifies the relationship between the transformations; (b) it contains an empirical study of what can be gained by applying the transformations; and (c) it provides some guidance on the kinds of problems that are likely to benefit from the transformations.
Cite
Text
Costa et al. "Query Transformations for Improving the Efficiency of ILP Systems." Journal of Machine Learning Research, 2003.Markdown
[Costa et al. "Query Transformations for Improving the Efficiency of ILP Systems." Journal of Machine Learning Research, 2003.](https://mlanthology.org/jmlr/2003/costa2003jmlr-query/)BibTeX
@article{costa2003jmlr-query,
title = {{Query Transformations for Improving the Efficiency of ILP Systems}},
author = {Costa, Vítor Santos and Srinivasan, Ashwin and Camacho, Rui and Blockeel, Hendrik and Demoen, Bart and Janssens, Gerda and Struyf, Jan and Vandecasteele, Henk and Van Laer, Wim},
journal = {Journal of Machine Learning Research},
year = {2003},
pages = {465-491},
volume = {4},
url = {https://mlanthology.org/jmlr/2003/costa2003jmlr-query/}
}