Abstract
Abstract extraction of traditional English teaching texts usually has some problems such as incomplete resource integration and poor resource scheduling. In view of this situation, this paper uses parallel corpus to improve the extraction model of text abstract in English teaching, and improves the relevant modules of original text abstract in English teaching, thus effectively improving the extraction effect of text abstract. In this algorithm, association rules are adopted to process the abstracts, analyze the features of the samples, extract the features of English short sentences and sentences, and finally improve the accuracy of text extraction. This paper studies the method of parallel corpus, improves the data model of text abstract extraction in English teaching, and reveals the working principle and mechanism of text abstract extraction in English teaching. The data test shows that using parallel corpus to create a text abstract extraction model in English teaching has excellent performance in the extraction of text abstract in English teaching.
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