Research on Automatic Generation of English Teaching Information Based on Automatic Extraction of Web Information

In order to improve the efficiency and quality of automatic generation of English teaching information and achieve the ideal effect of generating accurate teaching information in a fast time, automatic extraction of Web information is introduced, and the research on automatic generation of English teaching information based on automatic extraction of Web information is carried out. First, we use data amplification method to preprocess English teaching information and construct pseudo parallel sentences. Secondly, the context of teaching information is coded, and the distance calculation between any two positions of English teaching information is reduced to a constant through the attention mechanism to solve the problem of long-distance dependence of information. Then, a corpus of English teaching information is built to store and manage the relevant contents, such as morphological reduction, parts-of-speech tagging, syntactic structure tagging, etc. Finally, the semantic relation of English teaching information is automatically extracted from Web information, and the teaching information is automatically generated. The experimental results show that with the increase of test data in English corpus, the F-value reaches more than 96%, and the accuracy rate of information generation and recall rate are higher.