Patent ID: 11934790
Assignee: BOE TECHNOLOGY GROUP CO., LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 8:
9. A method of training a neural network, wherein the neural network comprises a generative network, a first branch network, a first classification network, a second branch network and a second classification network; the training method comprises a semantic classification training stage; wherein,
the semantic classification training stage comprises:
inputting a first training remark relating to a first object, extracting a first training common representation vector by processing the first training remark using the generative network, extracting a first training single representation vector by processing the first training remark using the first branch network, obtaining a first training representation vector by splicing the first training common representation vector and the first training single representation vector, and obtaining a predicted class label of semantic classification of the first training remark by processing the first training representation vector using the first classification network;
inputting a second training remark relating to a second object, extracting a second training common representation vector by processing the second training remark using the generative network, extracting a second training single representation vector by processing the second training remark using the second branch network, obtaining a second training representation vector by splicing the second training common representation vector and the second training single representation vector, and obtaining a predicted class label of semantic classification of the second training remark by processing the second training representation vector using the second classification network;
calculating a system loss value through a system loss function based on the predicted class label of the first training remark and the predicted class label of the second training remark; and
correcting parameters of the generative network, the first branch network, the first classification network, the second branch network and the second classification network based on the system loss value;
wherein the first object and the second object are associated remarked objects.