Data Analysis and Optimization of English Reading Corpus Based on Feature Extraction

In order to solve the difficulties faced by English reading teaching, this paper proposes a feature extraction-oriented method for data analysis and optimization of English reading corpus. This method specifically includes the evaluation of vocabulary coverage, comparing the value and vocabulary distribution evaluation of the two sets of textbooks in helping students master English core vocabulary and adapt to the English reading environment as soon as possible, testing whether the teaching of the three sets of textbooks can enable learners to reach the level of free reading corresponding English materials, and testing whether the gradient of the textbooks can be in line with the average language level required for reading corresponding English materials. The experimental results show that, compared with the blog-1565 based on the four authoritative core word lists, the English core word coverage of the two tutorials has reached 91.8% and 93.7%, respectively, and can be improved to 96% and 97.4%, respectively, after optimization. Conclusion. It is proved that the data analysis and optimization of English reading corpus based on feature extraction can play a directional role in the current English reading-related textbooks.