Patent ID: 11972218
Assignee: JINAN UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 9:
10. The specific target-oriented social media tweet sentiment analysis method as claimed in claim 1, wherein the combining the self-attention result with the specific target word vector and passing through a cross-attention structure to obtain cross-attention results comprises:
using the specific target word vector to perform cross-attention operations with the local self-attention result and the position self-attention result individually as follows:, Attention
   
    c
    ⁢
    r
    ⁢
    o
    ⁢
    s
    ⁢
    s
   
  
  =
  
   
    softmax
    (
    
     
      T
      ·
      
       K
       c
       T
      
     
     
      d
     
    
    )
   
   ⁢
   
    V
    c
   
  
 

where, T represents a result of the specific target word vector passing through a parameterization matrix, Kc and Vc respectively represent results of passing the local self-attention result through two parameterization matrices individually;
using different parameterization matrices to obtain multi-head cross-attention results, and using a parameterization matrix after concatenation of the multi-head cross-attention results to reduce a dimensionality of the result and thereby obtain a cross-attention result of the specific target vector and the local self-attention result; and
modifying Kc and Vc as results of passing the position self-attention result through two parameterization matrices individually, to obtain a cross-attention result of the specific target vector and the position self-attention result;
wherein the attention representation matrix is obtained by concatenating the cross-attention result of the local self-attention result and the cross-attention result of the position self-attention result.