Korean grammar error recognition algorithm based on big data corpus and semantic analysis is studied in this paper. Data mining directly faces massive data, and there are also some various complex relationships between these data, which leads to the surge of search space and search dimension in the mining process. Based on the traditional methods, the semantic analysis and the big data framework are combined to construct framework for the recognition algorithm. The component analysis method is mainly used in the field of word meaning research, and its use premise is to divide the word meaning into different semantic components, this model is applied into the grammar error recognition. The performance of the model is efficient, and the application scenarios are discussed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Korean Grammar Error Recognition Algorithm Based on Big Data Corpus and Semantic Analysis


    Contributors:


    Publication date :

    2021-12-02


    Size :

    847638 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Grammar-Constrained Neural Semantic Parsing with LR Parsers

    Baranowski, Artur / Hochgeschwender, Nico | German Aerospace Center (DLR) | 2021

    Free access

    Mining Layered Grammar Rules for Action Recognition

    Wang, L. / Wang, Y. / Gao, W. | British Library Online Contents | 2011


    Vehicular speech recognition grammar selection based upon captured or proximity information

    GRAUMANN DAVID L / ROSARIO BARBARA | European Patent Office | 2016

    Free access