公开(公告)号：US10901971B2

公开(公告)日：2021-01-26

申请号：US16736603

申请日：2020-01-07

Applicant: ADVANCED NEW TECHNOLOGIES CO., LTD.

Inventor： Shaosheng Cao ,  Xinxing Yang ,  Jun Zhou

IPC: G06F16/00 ,  G06F16/22 ,  G06F16/27 ,  G06F16/901 ,  H04L29/08

Abstract: Embodiments of the present specification disclose random walking and a cluster-based random walking method, apparatus and device. A solution includes: obtaining information about each node included in graph data, generating, according to the information about each node, a hash table reflecting a correspondence between the node and an adjacent node of the node, and generating a random sequence according to the hash table, to implement random walking in the graph data. The solution is applicable to clusters and single machines.

公开(公告)号：US11257007B2

公开(公告)日：2022-02-22

申请号：US16587977

申请日：2019-09-30

Applicant: Advanced New Technologies Co., Ltd.

Inventor： Xinxing Yang ,  Shaosheng Cao ,  Jun Zhou ,  Xiaolong Li

IPC: G06N20/00 ,  G06F17/16 ,  G06F17/18 ,  G06K9/62

Abstract: An N×M dimensional target matrix is generated based on N data samples and M dimensional data features respectively corresponding to the N data samples. Encryption calculation is performed on the N×M dimensional target matrix based on a Principal Component Analysis (PCA) algorithm to obtain an N×K dimensional encryption matrix K is less than M. The N×K dimensional encryption matrix is transmitted to a modeling server. The modeling server trains a machine learning model by using the N×K dimensional encryption matrix as a training sample.

公开(公告)号：US11269966B2

公开(公告)日：2022-03-08

申请号：US16918869

申请日：2020-07-01

Applicant: Advanced New Technologies Co., Ltd.

Inventor： Xinxing Yang ,  Jun Zhou ,  Xiaolong Li

IPC: G06F16/00 ,  G06F16/9535 ,  G06K9/62

Abstract: The present specification discloses a multi-classifier-based recommendation method and device, and an electronic device. In the method, a target sub-classifier is obtained from k sub-classifiers in a multi-classifier based on received data, where the target sub-classifier is a sub-classifier whose data distribution has a highest similarity with feature data in the multi-classifier; the first prediction data obtained after the primary classifier performs prediction on the feature data is obtained, the second prediction data obtained after the target sub-classifier performs prediction on the feature data is obtained, and then the third prediction data is obtained by combining the first prediction data and the second prediction data, so that more accurate prediction data is obtained, thereby resolving the technical problem of low accuracy of data classification prediction in the existing technology; and the feature data is recommended based on the third prediction data, so that the accuracy of data recommendation is improved.

公开(公告)号：US11074246B2

公开(公告)日：2021-07-27

申请号：US16805079

申请日：2020-02-28

Applicant: Advanced New Technologies Co., Ltd.

Inventor： Shaosheng Cao ,  Xinxing Yang ,  Jun Zhou

IPC: G06F16/23 ,  G06F16/22

Abstract: Implementations of the present specification disclose method, apparatus, and device for processing graph data using a random walk-based process. The process is applicable to either a cluster of machines, a stand-alone machine, or both. In one aspect, the method includes: obtaining, by a cluster, data describing a graph that has nodes and edges between the nodes, wherein the cluster comprises (i) a server cluster that includes a plurality of server machines and (ii) a working machine cluster that includes a plurality of working machines; generating a two-dimensional array based on the data, wherein generating the two-dimensional array comprises generating, for each node included in the graph, a row comprising respective identifiers of adjacent nodes of the node; and generating, based on the two-dimensional array, a random sequence that represents a random walk processing of the data by the cluster.