US 11,989,260 B2
Data-sharing systems and methods, which use multi-angle incentive allocation
Chendi Wang, Vancouver (CA); Amin Banitalebi, Vancouver (CA); Lanjun Wang, Burnaby (CA); and Yong Zhang, Richmond (CA)
Assigned to HUAWEI CLOUD COMPUTING TECHNOLOGIES CO., LTD., Gui'an New District (CN)
Filed by HUAWEI CLOUD COMPUTING TECHNOLOGIES CO., LTD., Gui'an New District (CN)
Filed on Jun. 30, 2021, as Appl. No. 17/363,871.
Prior Publication US 2023/0015813 A1, Jan. 19, 2023
Int. Cl. G06N 20/00 (2019.01); G06F 18/2113 (2023.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01)
CPC G06F 18/214 (2023.01) [G06F 18/2113 (2023.01); G06F 18/23 (2023.01); G06N 20/00 (2019.01)] 23 Claims
OG exemplary drawing
 
17. A computerized method for sharing data from one or more data providers to one or more data consumers, the data comprising one or more input datasets each provided by a respective one of the one or more data providers, the method comprising:
obtaining one or more training datasets from the one or more input datasets, each of the one or more training datasets corresponding to a respective one of the one or more input datasets;
evaluating the one or more training datasets for generating one or more quality scores, each quality score associated with a respective one of the one or more training datasets;
generating a unit value for each of the one or more input datasets based on the one or more quality scores;
receiving incentives from the one or more data consumers for acquiring at least a portion of the input datasets;
distributing the received incentives to the one or more data providers based on the one or more unit values and the at least portion of the input datasets; and
sharing the at least portion of the input datasets with the one or more data consumers;
wherein said evaluating the one or more training datasets comprises: evaluating the one or more training datasets using a first evaluation method comprising:
training an artificial intelligence AI model using the one or more training datasets and a machine learning algorithm to obtain one or more first trained models, and
generating each of the one or more quality scores based on one or more first predictions generated by a corresponding one of the one or more first trained models using one or more test datasets received from the one or more data consumers.