Method and apparatus for learning a model to generate poi data using federated learning

A method for training a model for creating POI data on a server through federated learning, the method comprising:

• transmitting a first common prediction model enabling a terminal to create POI data;
• transmitting hyper-parameters to enable a terminal to train the first common prediction model;
• receiving weight-parameters from the terminal;
• and
• training the first common prediction model using the weight-parameters,
• wherein the first common prediction model is transmitted to one or more terminals.

A terminal for training a model for creating POI data through federated learning, the method comprising:

• a transceiver;
• a memory;
• a display;
• and
• a processor,
• wherein, through the transceiver, the processor receives an SMS (short message service) message for notifying that a user of the terminal has made a payment, feeds the SMS message into a store information extraction model and acquires store information from an output of the store information extraction model, acquires current location information of the terminal, caches POI (point of interest) data, which is the location information labeled with the stored information, and trains a first common prediction model using the POI data,
• wherein the first common prediction model is received through a server, and the SMS message contains text information indicating the business name of the store where the user has made the payment.