College entrance examination plan admission data benchmarking method based on GloVe algorithm

The invention relates to the field of natural language processing, and discloses a GloVe algorithm-based college entrance examination plan admission data benchmarking method, which comprises the following steps of S1, collecting college entrance examination related text data; s2, performing preprocessing and word segmentation processing on the text data to form a corpus, and converting original text data into a form which can be processed by a model; s3, constructing a GloVe algorithm model by taking the corpus as a data basis; and S4, performing data benchmarking. According to the method, on the basis of machine learning, big data analysis and natural language processing, the purpose of automatically and intelligently completing benchmarking work of college entrance examination plan admission data is achieved by adopting the GloVe algorithm, a large amount of manpower and time cost is saved, the data benchmarking efficiency and accuracy are improved, and the data benchmarking efficiency and accuracy are impr