The invention discloses a personality evaluation-oriented big
language model enhanced text mapping
processing method and
system. The method comprises the following steps: S1, constructing a correlation
model sample database; constructing a BERT model to obtain text features of user social text data, and then performing average
pooling processing to obtain an initial vector; s2, firstly performing social text data splicing
processing, and performing extraction embedding processing and average
pooling processing through a Llama3 model to obtain a user integration vector; s3, constructing a fusion model containing three full connection
layers and an attention mechanism, and carrying out addition fusion to obtain a final user vector; and S4, performing personality
label interpretation and coding by using a GPT-4 model and a BERT model, and performing contrast learning model training by using a target
label contrast learning model. According to the method, the
model sample database is used for carrying out model processing and relation training of the BERT model, the Llama3 model, the fusion model, the target
label comparison learning model and the like, and the learning precision and efficiency of the user vector and personality label relation model are remarkably improved.