Learning to normalize text from few examples

    Research output: Contribution to conferenceAbstractOther research output

    Abstract

    I propose a text normalization model based on learning edit operations from labeled data while incorporating features induced from unlabeled text and from dictionaries. These features enable effective learning with little supervision, as demonstrated on an English tweet normalization dataset.
    Original languageEnglish
    Publication statusPublished - 2014
    EventATILA 2014 - Ghent, Belgium
    Duration: 20 Nov 201421 Nov 2014

    Conference

    ConferenceATILA 2014
    CountryBelgium
    CityGhent
    Period20/11/1421/11/14

    Fingerprint

    normalization
    dictionary
    learning
    supervision

    Cite this

    Chrupala, G. (2014). Learning to normalize text from few examples. Abstract from ATILA 2014, Ghent, Belgium.
    Chrupala, Grzegorz. / Learning to normalize text from few examples. Abstract from ATILA 2014, Ghent, Belgium.
    @conference{c98f56614e724412bdb3344f7c2850d6,
    title = "Learning to normalize text from few examples",
    abstract = "I propose a text normalization model based on learning edit operations from labeled data while incorporating features induced from unlabeled text and from dictionaries. These features enable effective learning with little supervision, as demonstrated on an English tweet normalization dataset.",
    author = "Grzegorz Chrupala",
    year = "2014",
    language = "English",
    note = "ATILA 2014 ; Conference date: 20-11-2014 Through 21-11-2014",

    }

    Chrupala, G 2014, 'Learning to normalize text from few examples' ATILA 2014, Ghent, Belgium, 20/11/14 - 21/11/14, .

    Learning to normalize text from few examples. / Chrupala, Grzegorz.

    2014. Abstract from ATILA 2014, Ghent, Belgium.

    Research output: Contribution to conferenceAbstractOther research output

    TY - CONF

    T1 - Learning to normalize text from few examples

    AU - Chrupala, Grzegorz

    PY - 2014

    Y1 - 2014

    N2 - I propose a text normalization model based on learning edit operations from labeled data while incorporating features induced from unlabeled text and from dictionaries. These features enable effective learning with little supervision, as demonstrated on an English tweet normalization dataset.

    AB - I propose a text normalization model based on learning edit operations from labeled data while incorporating features induced from unlabeled text and from dictionaries. These features enable effective learning with little supervision, as demonstrated on an English tweet normalization dataset.

    M3 - Abstract

    ER -

    Chrupala G. Learning to normalize text from few examples. 2014. Abstract from ATILA 2014, Ghent, Belgium.