The application relates to a text semantic communication method based on joint
knowledge graph learning, which comprises the following steps: completing the alignment of entities, relations and entity attributes in a
knowledge graph library between user terminals through a
secure hash algorithm; using a
generative adversarial network to unify the embedding representation of different user terminal
knowledge graph libraries; a user terminal compresses a to-be-transmitted text into semantic triples and matches a similar semantic triple set from a local knowledge graph
library; the similar semantic triples are encoded and sent to a receiving terminal; the receiving terminal
decodes the received message to obtain a similar semantic triple set; the similarity between the similar semantic triple and the local knowledge graph
library is calculated by using a string similarity
algorithm, the most similar triple is selected as the recovered semantic triple; and a fine-tuned semantic
recovery module is used to convert the recovered semantic triple into a recovered text and recover the to-be-transmitted text, so that the safety and privacy of semantic transmission can be improved.