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

Claim 1:
2. The address information feature extraction method based on a deep neural network model according to claim 1, wherein in the step S1, a specific execution flowchart in the word embedding module comprises steps of:
S11: creating a dictionary-vector conversion matrix C;
S12: getting an index char_index of each of the address characters in the input address text in the dictionary;
S13: obtaining a one-hot vector of each of the characters according to the index, and a length of the vector being a size of the dictionary;
S14: multiplying the one-hot vector with the Lookup Table, to obtain a word embedding value embedding0 of each of the characters:
S15: obtaining a position position of each of the characters in the address text;
S16: obtaining a position weight vector of each of the characters according to the position coding algorithm, wherein a position weight vector PW of each of the characters is composed of position weight values of all dimensions;
a position weight value of an even-numbered dimension is:, PW
   ⁡
   (
   
    position
    ,
    
     
      i
      |
      
       i
       ⁢
          
       %2
      
     
     =
     0
    
   
   )
  
  =
  
   sin
   (
   
    position
    /
    
     10000
     
      i
      
       d
       model
      
     
    
   
   )
  
 

a position weight value of an odd-numbered dimension is:, PW
   ⁡
   (
   
    position
    ,
    
     
      i
      |
      
       i
       ⁢
          
       %2
      
     
     =
     1
    
   
   )
  
  =
  
   cos
   (
   
    position
    /
    
     10000
     
      
       i
       -
       1
      
      
       d
       model
      
     
    
   
   )
  
 

where, dmodel represents a dimension of word embedding embedding0, and i represents an i-th dimension that is calculated; and
S17: adding the position weight vector and the word embedding value of each of the characters, to obtain a character vectorization expression content of each of the characters weighted by the position sequence:

embedding=embedding0+PW.