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

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.