Research on enterprise classification of ERNIE-textCNN fusion focal loss

Abstract

Enterprise information contains a large amount of valuable content. Analyzing enterprise information and clarifying the structure of the industry chain in which the enterprise is located can provide assistance in optimizing the structure of the industry chain. For this reason, this article proposes an enterprise classification model that integrates focal loss and ERNIE-textCNN to classify enterprises. The attention mechanism and textCNN are used to extract semantic features at different levels to solve the problem of missing features and contextual semantic relationships in enterprise short text data. To address the imbalance in enterprise data, the loss function in the model is modified to focal loss function. Experimental verification shows that in all samples, the classification accuracy of a small sample category can be improved by 10%.Finally, the enterprise is matched to the industrial chain graph.