公开(公告)号：US11106804B2

公开(公告)日：2021-08-31

申请号：US16720931

申请日：2019-12-19

Applicant: Advanced New Technologies Co., Ltd.

Inventor： Peilin Zhao ,  Jun Zhou ,  Xiaolong Li ,  Longfei Li

IPC: G06F21/60 ,  G06N3/063 ,  G06N5/04 ,  G06N20/00 ,  G06Q10/10 ,  G06Q10/06

Abstract: Techniques for data sharing between a data miner and a data provider are provided. A set of public parameters is downloaded from the data miner. The public parameters are data miner parameters associated with a feature set of training sample data. A set of private parameters in the data provider can be replaced with the set of public parameters. The private parameters are data provider parameters associated with the feature set of training sample data. The private parameters are updated to provide a set of update results. The private parameters are updated based on a model parameter update algorithm associated with the data provider. The update results is uploaded to the data miner.

公开(公告)号：US11244402B2

公开(公告)日：2022-02-08

申请号：US16022194

申请日：2018-06-28

Applicant: Advanced New Technologies Co., Ltd.

Inventor： Yuxiang Lei ,  Guanru Li ,  Wei Ding ,  Jing Huang ,  Chunping Tan ,  Shiyi Chen ,  Mingqian Shi ,  Peilin Zhao ,  Longfei Li ,  Zhiqiang Zhang

IPC: G06Q40/08 ,  G06K9/62 ,  G06N3/02 ,  H04L29/08

Abstract: A plurality of variable data of personal attribute information associated with at least one vehicle insurance user is received at a prediction server. Based on a service scenario requirement, a pre-constructed prediction algorithm is selected. The plurality of variable data is processed by one or more processors using the pre-constructed prediction algorithm. At least one prediction result is generated as the prediction server.

公开(公告)号：US11106802B2

公开(公告)日：2021-08-31

申请号：US16053606

申请日：2018-08-02

Applicant: Advanced New Technologies Co., Ltd.

Inventor： Peilin Zhao ,  Jun Zhou ,  Xiaolong Li ,  Longfei Li

IPC: G06N3/063 ,  G06N5/04 ,  G06N20/00 ,  G06F21/60 ,  G06Q10/10 ,  G06Q10/06

Abstract: Techniques for data sharing between a data miner and a data provider are provided. A set of public parameters is downloaded from the data miner. The public parameters are data miner parameters associated with a feature set of training sample data. A set of private parameters in the data provider can be replaced with the set of public parameters. The private parameters are data provider parameters associated with the feature set of training sample data. The private parameters are updated to provide a set of update results. The private parameters are updated based on a model parameter update algorithm associated with the data provider. The update results is uploaded to the data miner.