Abstract: In order to solve the problem of implicit opinion targets recognition in course comments，a method of implicit opinion targets identification based on text classification was proposed in this paper． First，the word vectors corresponding to the training text were obtained by word2vec model which produced the short text features． Then，TextCNN was used to extract high-level features by obtainning classification model by pooling K-max and putting it into softmax classifier． Finally，the trained classifier was used to classify the implicit opinion sentences，and the corresponding opinion targets of the implicit opinion sentences were obtained． The experiment results show that the attribute classification of implicit curriculum reviews based on the convolutional neural network，the accuracy rate of implicit opinion targets identification in curriculum reviews is 89． 9%，which meets the needs of implicit opinion sentence in curriculum reviews．

Key words: implicit opinion targets, convolutional neural network, text classification, word embedding