English Writing Teaching Model Dependent on Computer Network Corpus Drive Model

Abstract

At present, the mainstream lexicalized English writing methods take only the corpus dependence between words into consideration, without introducing the corpus collocation and other issues. “Drive” is a relatively essential feature of words. And once the drive structure of a word is determined, it will be relatively clear what kinds of words to collocate with, hence the structure of the sentence can be derived relatively directly. In this paper, the English writing model that relies on the computer network corpus drive model is put forward. In this model, rich English corpus is introduced in the decomposition of the rules and the calculation of the probability, which includes not only the corpus dependence information, but also the drive structure and other corpus collocation information. Improved computer network corpus drive model is used to carry out the English writing teaching experiment. The experimental results show that the precision and the recall rate are 88.76% and 87.43%, respectively. The F value of the comprehensive index is improved by 6.65% compared with the Collins headword driven English modes of writing.