Samsung patents smart home control suggestions based on past habits

1. An electronic device comprising: an interface; a memory configured to store a learning model; and a processor configured to provide a control recommendation for an external electronic device by using the learning model stored in the memory, wherein the learning model comprises: an input layer that generates a plurality of first embedding vectors corresponding to an input sequence including a series of control histories of a user on a plurality of external electronic devices by applying embedding weights to the input sequence, a first encoding layer that outputs a plurality of first output vectors by using one or more transformers to generate a plurality of respective first encoded vectors from the plurality of first embedding vectors, applying first weights to the plurality of first encoded vectors, and adding the plurality of first encoded vectors to which the first weights have been applied, and a second encoding layer that outputs a second output vector by adding position information to the plurality of first output vectors to generate a plurality of second embedding vectors, using the one or more transformers to generate a plurality of second encoded vectors from the plurality of second embedding vectors, applying second weights to values of the plurality of second encoded vectors, and adding the plurality of second encoded vectors to which the second weights have been applied, wherein the first weights are based on a query vector and first trained parameters, wherein the second weights are based on time information and second trained parameters, and wherein the first trained parameters and the second trained parameters are learned such that a loss between training data for the learning model and the control recommendation based on the learning model is minimized.