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US 12,118,042 B2Granted
Method, system, and non-transitory computer-readable record medium for providing multiple models of federated learning using personalization
AssigneeLINE Plus Corporation
InventorHyukjae Jang
Life of this patent
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Abstract
Disclosed is a method, system, and non-transitory computer-readable record medium for providing a multi-model through federated learning using personalization. The method includes classifying users into a plurality of groups; and generating a prediction model for a service as a multi-model through federated learning for each of the plurality of groups.
Claims15
A method performed by a computer system comprising at least one processor configured to execute computer-readable instructions comprised in a memory, the method comprising:
- by the at least one processor,
- distributing an initial model generated by the computer system to electronic devices of users;
- classifying the users into a plurality of groups, at least one first user among the users being classified into at least two groups such that the first user belongs to all of the two groups;
- and
- generating a prediction model for a service as a multi-model through federated learning for each of the plurality of groups,
- wherein the generating of the prediction model for the service comprises
- generating a corresponding group model, for each of the plurality of groups, by collecting, into a single model of the multi-model, models trained by the electronic devices of the users belonging to a corresponding group through the federated learning,
- distributing the corresponding group model to the electronic devices of the users belonging to the corresponding group, each of at least two corresponding group models corresponding to the two groups being distributed to an electronic device of the first user, the at least two corresponding group models including a first group model related to a first chatroom where the first user participates and a second group model related to a second chatroom where the first user participates, the first group model being trained based on data associated with the first chatroom in the electronic device of the first user and first update data associated with the first chatroom for the first group model being received from the electronic device of the first user, and the second group model trained being based on data associated with the second chatroom in the electronic device of the first user and second update data associated with the second chatroom for the second group model being received from the electronic device of the first user, and
- improving the corresponding group model based on the update data about the corresponding group model received from the electronic devices of the users belonging to the corresponding group,
- wherein the first group model is improved based on a first update data set of the update data including the first update data and the second group model is improved based on a second update data set of the update data including the second update data.
7 more elements
A computer system comprising:
- at least one processor configured to execute computer-readable instructions comprised in a memory,
- wherein the at least one processor is configured to
- provide an initial model generated by the computer system to electronic devices of users;
- classify the users into a plurality of groups, at least one first user among the users being classified into at least two groups such that the first user belongs to all of the two groups;
- and
- generate a prediction model for a service as a multi-model through federated learning for each of the plurality of groups and to provide the generated prediction model,
- wherein, for generating the prediction model, the at least one processor is configured to generate a corresponding group model, for each of the plurality of groups, by collecting, into a single model of the multi-model, models trained by the electronic devices of the users belonging to a corresponding group through the federated learning,
- distribute the corresponding group model to the electronic devices of the users belonging to the corresponding group, each of at least two corresponding group models corresponding to the two groups being distributed to an electronic device of the first user and said each of the two corresponding group models being individually trained based on data corresponding to a respective group model of the two corresponding group models in the electronic device of the first user to generate update data about said each of the two corresponding group models, the at least two corresponding group models including a first group model related to a first chatroom where the first user participates and a second group model related to a second chatroom where the first user participates, the first group model being trained based on data associated with the first chatroom in the electronic device of the first user and first update data associated with the first chatroom for the first group model being received from the electronic device of the first user, and the second group model being trained based on data associated with the second chatroom in the electronic device of the first user and second update data associated with the second chatroom for the second group model being received from the electronic device of the first user and
- improve the corresponding group model based on update data about the corresponding group model received from the electronic devices of the users belonging to the corresponding group,
- wherein the first group model is improved based on a first update data set of the update data including the first update data and the second group model is improved based on a second update data set of the update data including the second update data.
7 more elements
Dependencies are inferred from the claim text.