Patent ID: 11941522
Assignee: ZHEJIANG UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. The address information feature extraction method based on a deep neural network model according to claim 1, wherein a specific implementation process of the step S6 comprises steps of:
S61: transplanting the word embedding module and the feature extraction module in the address language model trained in the step S4, and connecting the two to form an encoder; and
S62: reconstructing a target task module that is used to classify the address text as a decoder, for generating a probability distribution for output of the encoder through the neural network; in the decoder,
first, performing average pooling on output SAN of the last layer of self-transformer sub-module of the feature extraction module in the encoder, and the pooling result serving as a semantic feature of the address sentence;
then performing, through the feed forward network layer, nonlinear transformation on the semantic feature of the address sentence, to convert the semantic feature into the probability distribution feature of a classification problem, wherein an activation function uses tanh;
finally converting, through a fully-connected-layer, the obtained probability distribution feature into probability score distribution of the address text, and the predicted probability distribution P (B|W) of the address text belonging to each cluster obtained in the step S5 from the softmax function.