Distributional Learning of Simple Context-Free Tree Grammars
Abstract
This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a substructure and the remaining structure, and on their interrelations. A corresponding learning algorithm can emulate those relations in order to determine a correct grammar for the target language.
Cite
Text
Kasprzik and Yoshinaka. "Distributional Learning of Simple Context-Free Tree Grammars." International Conference on Algorithmic Learning Theory, 2011. doi:10.1007/978-3-642-24412-4_31Markdown
[Kasprzik and Yoshinaka. "Distributional Learning of Simple Context-Free Tree Grammars." International Conference on Algorithmic Learning Theory, 2011.](https://mlanthology.org/alt/2011/kasprzik2011alt-distributional/) doi:10.1007/978-3-642-24412-4_31BibTeX
@inproceedings{kasprzik2011alt-distributional,
title = {{Distributional Learning of Simple Context-Free Tree Grammars}},
author = {Kasprzik, Anna and Yoshinaka, Ryo},
booktitle = {International Conference on Algorithmic Learning Theory},
year = {2011},
pages = {398-412},
doi = {10.1007/978-3-642-24412-4_31},
url = {https://mlanthology.org/alt/2011/kasprzik2011alt-distributional/}
}