Abstract: Because the existing algorithms fail to calculate the semantic similarity, the detection results are not ideal, and an automatic detection algorithm for the deviation of the composition subject for college English teaching is proposed. In the college English teaching environment, combining distributed semantic space and structured semantic space, a semantic representation model is constructed to obtain the semantic similarity between English words and phrases. Through the LDA(Latent Dirichlet Allocation) model, all documents are trained, and the probabilistic weighted summation of each subject and feature words in the document is carried out, and the composition of the subject deviation is detected according to the set reasonable threshold. The results of simulation experiments show that the proposed algorithm can obtain high-precision automatic detection results of composition subject deviation.

Key words: college english teaching,  , composition theme,  , deviation,  , automatic detection