Two Approaches for Building an Unsupervised Dependency Parser and Their Other Applications
Abstract
Much work has been done on building a parser for natural languages, but most of this work has concen-trated on supervised parsing. Unsupervised parsing is a less explored area, and unsupervised dependency parser has hardly been tried. In this paper we present two approaches for building an unsupervised dependency parser. One approach is based on learning dependency relations and the other on learning subtrees. We also propose some other applications of these approaches.
Cite
Text
Gorla et al. "Two Approaches for Building an Unsupervised Dependency Parser and Their Other Applications." AAAI Conference on Artificial Intelligence, 2007.Markdown
[Gorla et al. "Two Approaches for Building an Unsupervised Dependency Parser and Their Other Applications." AAAI Conference on Artificial Intelligence, 2007.](https://mlanthology.org/aaai/2007/gorla2007aaai-two/)BibTeX
@inproceedings{gorla2007aaai-two,
title = {{Two Approaches for Building an Unsupervised Dependency Parser and Their Other Applications}},
author = {Gorla, Jagadeesh and Goyal, Amit and Sangal, Rajeev},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2007},
pages = {1860-1861},
url = {https://mlanthology.org/aaai/2007/gorla2007aaai-two/}
}