Patent ID: 11941513
Assignee: KOREA ADVANCED INSTITUTE OF SCIENCE AND TECHNOLOGY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 15:
16. A method of operating a device for ensembling data received from a plurality of prediction devices, the method comprising:
providing time series data and a prediction request to a first prediction device and a second prediction device;
receiving a first device prediction result of the time series data that is responsive to the prediction request, from the first prediction device;
receiving a second device prediction result of the time series data that is responsive to the prediction request, from the second prediction device;
preprocessing, using a preprocessor of a predictor, the first and second device prediction results;
generating, using an item weight calculator of the predictor, first item weights that depend on first item values of the first and second device prediction results, based on the preprocessed first and second device prediction results;
generating, using the item weight calculator of the predictor, second item weights that depend on second item values of the first and second device prediction results, based on the preprocessed first and second device prediction results;
generating, using a device weight calculator of the predictor, a first device weight corresponding to the first prediction device and a second device weight corresponding to the second prediction device, based on the preprocessed first and second device prediction results;
generating, using a weight applicator of the predictor, a first result by applying the first and second item weights and the first device weight to the preprocessed first device prediction result;
generating, using the weight applicator of the predictor, a second result by applying the first and second item weights and the second device weight to the preprocessed second device prediction result; and
generating an ensemble result, by the predictor using a prediction model, based on the first result and the second result,
wherein the item weight calculator includes a neural network that includes a first input layer, a first embedding layer, and a first attention layer, and
wherein generating the first item weights, using the item weight calculator, includes:
receiving, by the first input layer, the first item values;
outputting, by the first embedding layer, a first intermediate result in consideration of a relationship between the first item values;
analyzing, by the first attention layer, the first intermediate result; and
calculating, by the first attention layer, the first item weights using an attention mechanism.