Towards Unsupervised Learning of Constructions From Text

Reference:

Krista Lagus, Oskar Kohonen, and Sami Virpioja. Towards unsupervised learning of constructions from text. In Magnus Sahlgren and Ola Knutsson, editors, Proceedings of the Workshop on Extracting and Using Constructions in NLP of 17th Nordic Conference on Computational Linguistics, NODALIDA, May 2009. SICS Technical Report T2009:10.

Abstract:

Statistical learning methods offer a route for identifying linguistic constructions. Phrasal constructions are interesting both from the viewpoint of cognitive modeling and for improving NLP applications such as machine translation. In this article, an initial model structure and search algorithm for attempting to learn constructions from plain text is described. An information-theoretic optimization criteria, namely the Minimum Description Length principle, is utilized. The method is applied to a Finnish corpus consisting of stories told by children.

Suggested BibTeX entry:

@inproceedings{lagusokohonenvirpioja_2009,
    author = {Krista Lagus and Oskar Kohonen and Sami Virpioja},
    booktitle = {Proceedings of the Workshop on Extracting and Using Constructions in NLP of 17th Nordic Conference on Computational Linguistics, NODALIDA},
    editor = {Magnus Sahlgren and Ola Knutsson},
    month = {May},
    note = {SICS Technical Report T2009:10},
    title = {Towards Unsupervised Learning of Constructions From Text},
    year = {2009},
}