Intentional Recognition of Cotton Disease and Pest Questions Based on ERNIE and Improved DPCNN
Aiming at the problems that there is no publicly available question data set related to cotton pests and diseases,and the cotton pest and disease questions are short in length and various in type,the CQ-Cls data set of cotton pest and disease questions was established containing 78 species of disease and pest enti-ties and 9 types of questions.An intention recognition model of cotton disease and pest questions based on the ERNIE pre-training model was proposed.Firstly,the input questions were mapped into the vector space through the ERNIE model;secondly,the feature vector was extracted using the DPCNN model that fused word location information,which could effectively improve the expression ability compared with the basic DPCNN model;and then the final results could be obtained through Softmax.The test results showed that the intention recognition model proposed in this study achieved better results compared to other models,with the values of 97.45%and 97.31%for macro average and weighted average F1 score,respectively.On the DMSCD data set with complex and diverse text corpora and non-standard text formats,the average weight of F1 scores for differ-ent categories in the training results could also reach 73.42%,further proving the effectiveness and generaliza-tion ability of the model proposed in this paper.
Cotton pests and diseasesIntention recognition of questionsERNIE modelDPCNN mod-elWord location information