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

Claim 2:
3. The address information feature extraction method based on a deep neural network model according to claim 1, wherein in the step S3, a specific execution flowchart in the target task module comprises steps of:
S31: using output of the feature extraction module in the step S2 as input of the feed forward network layer, transforming, through nonlinear transformation, it into “corrected word embedding” information prob_embedding where each of the characters has been affected by the context, and a nonlinear transformation formula is:

prob_embedding=g(W×SA+b)

where g ( ) represents a ReLu function, W represents a weight matrix, and b represents linear offset;
S32: performing a linear transformation on prob_embedding, to obtain its probability distribution score:

logits=CT×prob_embedding+b′

where the weight matrix CT is transposition of the dictionary-vector conversion matrix C, and b′ represents offset of the linear transformation; and
S33: substituting the probability distribution score logits into a softmax activation function to finally obtain the conditional probability distribution where each of the characters is a respective word in the dictionary.

prob=softmax(logits)