Chinese word sense disambiguation method based on fusion of graph convolutional neural network and support vector machine

The invention relates to a Chinese word sense disambiguation method based on a graph convolutional neural network (GCN) fused with a support vector machine (SVM), in particular to a Chinese word sense disambiguation method based on the graph convolutional neural network (GCN) fused with the support vector machine (SVM) and a Chinese word sense disambiguation method based on the graph convolutional neural network (GCN) fused with the Chinese word sense disambiguation method based on the graph convolutional neural network (GCN) fused with the support vector machine (SVM). The method comprises the steps of firstly preprocessing corpora; and performing word segmentation, part-of-speech tagging and semantic tagging processing on statements of the training and testing corpora. A word sense disambiguation graph is constructed by taking sentences where ambiguous words are located and word forms, part-of-speech and semantic classes of vocabulary units on two sides of the ambiguous words as disambiguation features and