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

Claim 7:
8. The specific target-oriented social media tweet sentiment analysis method as claimed in claim 1, wherein the passing the target text word vectors through a self-attention structure containing position information to obtain a position self-attention result comprises:
making the target text word vectors contain the position information through a bidirectional long short-term memory (Bi-LSTM) network;
a forward LSTM comprising an input gate, a forget gate and an output gate, passing the target text word vectors through the forward LSTM to obtain a word vector {right arrow over (ht)}, processing the target text word vectors by a backward LSTM to obtain a word vector , and integrating the word vector {right arrow over (ht)} and word vector , wherein an integration function is as follows:

xt=f({right arrow over (ht)},

where, f is an operation of adding or concatenating into one vector, X={x1, x2, . . . , xn}represents a text vector containing position information;
performing a self-attention operation on the text vector, wherein an operation function is as follows:, Attention
    self
   
   =
   
    
     softmax
     (
     
      
       Q
       ·
       
        K
        T
       
      
      
       d
      
     
     )
    
    ⁢
    V
   
  
  ;
 

multiplying the text vector by three parameter matrices individually to obtain a query matrix Q, a key matrix K and a value matrix V, thereby obtaining a single-head self-attention result; and
obtaining a plurality of self-attention results by using different the query matrices, the key matrices and the value matrices, and performing concatenation and parameter matrix dimensionality-reduced projection on the plurality of self-attention results to obtain the position self-attention result.