Analogical Generalization of Linguistic Constructions
Abstract
Human language is extraordinarily creative in form and function, and adapting to this ever-shifting linguistic landscape is a daunting task for interactive cognitive systems. Recently, construction grammar has emerged as a linguistic theory for representing these complex and often idiomatic linguistic forms. Furthermore, analogical generalization has been proposed as a learning mechanism for extracting linguistic constructions from input. I propose an account that uses a computational model of analogy to learn and generalize argument structure constructions.
Cite
Text
McFate. "Analogical Generalization of Linguistic Constructions." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.9814Markdown
[McFate. "Analogical Generalization of Linguistic Constructions." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/mcfate2016aaai-analogical/) doi:10.1609/AAAI.V30I1.9814BibTeX
@inproceedings{mcfate2016aaai-analogical,
title = {{Analogical Generalization of Linguistic Constructions}},
author = {McFate, Clifton James},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2016},
pages = {4309-4310},
doi = {10.1609/AAAI.V30I1.9814},
url = {https://mlanthology.org/aaai/2016/mcfate2016aaai-analogical/}
}