@inproceedings{
    lagus+okohonen+virpioja_2009,
    editor = "Sahlgren, Magnus and Knutsson, Ola",
    author = "Lagus, Krista and Kohonen, Oskar and Virpioja, Sami",
    responsibleperson = "Lagus,Krista",
    title = "Towards Unsupervised Learning of Constructions From Text",
    booktitle = "Proceedings of the Workshop on Extracting and Using Constructions in NLP of 17th Nordic Conference on Computational Linguistics, NODALIDA",
    corerank = "NA",
    month = "May",
    note = "SICS Technical Report T2009:10",
    flags = "public AIRC copy",
    year = "2009",
    pdf = "nodalida2009.pdf",
    impactfactor = "A4",
    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."
}