公开(公告)号：US20240406121A1

公开(公告)日：2024-12-05

申请号：US18743335

申请日：2024-06-14

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Bingyang LIU ,  Weiyu JIANG ,  Bo CHEN ,  Chuang WANG ,  Fei YANG

IPC: H04L47/70 ,  H04L67/52

Abstract: An access control method includes: A computer device sends a source identifier and a target identifier to a first network device; and the first network device determines, based on the source identifier, the target identifier, and an access control list, an association attribute and a first target constraint item corresponding to the association attribute, determines a first verification code based on the association attribute and the first target constraint item corresponding to the association attribute, and then sends, to the computer device, first indication information that includes at least the first verification code. Then, the computer device determines the association attribute and first target information corresponding to the association attribute, adds, to a packet for accessing a target resource, the association attribute and the first target information corresponding to the association attribute, and sends the packet, where the packet further includes at least the first indication information.

公开(公告)号：US20240242127A1

公开(公告)日：2024-07-18

申请号：US18620051

申请日：2024-03-28

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Yichao WANG ,  Bo CHEN ,  Ruiming TANG ,  Xiuqiang HE ,  Hongkun ZHENG

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: This application discloses an information recommendation method, which may be applied to the field of artificial intelligence. The method includes: obtaining a target feature vector; and processing the target feature vector by using a recommendation model, to obtain recommendation information, where the recommendation model includes a cross network, a deep network, and a target network; the target network is used to perform fusion processing on a first intermediate output that is output by the first cross layer and a second intermediate output that is output by the first deep layer, to obtain a first fusion result, and the target network is further used to: process the first fusion result to obtain a first weight corresponding to the first cross layer and a second weight corresponding to the first deep layer, and weight the first fusion result with the first weight and the second weight separately.

公开(公告)号：US20230306077A1

公开(公告)日：2023-09-28

申请号：US18327584

申请日：2023-06-01

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Huifeng GUO ,  Bo CHEN ,  Ruiming TANG ,  Zhenguo LI ,  Xiuqiang HE

IPC: G06F17/18

CPC classification number: G06F17/18

Abstract: Embodiments of this application provide a data processing method and apparatus to better learn a vector representation value of each feature value in a continuous feature. The method specifically includes: The data processing apparatus obtains the continuous feature from sample data, and then performs discretization processing on the continuous feature by using a discretization model, to obtain N discretization probabilities corresponding to the continuous feature. The N discretization probabilities correspond to N preset meta-embeddings, and N is an integer greater than 1. Finally, the data processing apparatus determines a vector representation value of the continuous feature based on the N discretization probabilities and the N meta-embeddings.