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11.发明申请公开(公告)号：US20190043076A1
公开(公告)日：2019-02-07
申请号：US15865273
申请日：2018-01-09
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Zhenhua Dong , Zhirong Liu , Xiuqiang He , Ruiming Tang , Bohai Yang
Abstract: An advertisement management server in a communication system receives information of advertisements, determines an advertising value calculation policy, estimates a value of an advertising value element according to the information of each advertisement, calculates a value of each advertisement using the value of the advertising value element and the advertising value calculation policy as reference factors. The server instructs the communication system to broadcast the advertisements for displaying on the user terminals according to the calculated value of each advertisement.
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公开(公告)号：US20250148523A1
公开(公告)日：2025-05-08
申请号：US18989318
申请日：2024-12-20
Applicant: Huawei Technologies Co., Ltd.
Inventor： Wei Guo , Enming Yuan , Huifeng Guo , Ruiming Tang
IPC: G06Q30/0601
Abstract: An item recommendation method includes obtaining N pieces of first information, where an ith piece of first information indicates an ith first item and an ith behavior, the ith behavior is a behavior of a user for the ith item, N behaviors of the user correspond to M categories, i=1, . . . , N, N≥M, and M>1; processing the N pieces of first information based on a multi-head self-attention mechanism, to obtain N pieces of second information; and obtaining an item recommendation result based on the N pieces of second information, where the item recommendation result is used to determine, from K second items, a target item recommended to the user, and K≥1.
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公开(公告)号：US11586941B2
公开(公告)日：2023-02-21
申请号：US15931224
申请日：2020-05-13
Applicant: Huawei Technologies Co., Ltd.
Inventor： Jinkai Yu , Ruiming Tang , Zhenhua Dong , Yuzhou Zhang , Weiwen Liu , Li Qian
Abstract: A recommendation method includes generating a feature sequence based on to-be-predicted data of a user for a target object and according to a preset encoding rule, obtaining probability distribution information corresponding to each feature in the feature sequence, and obtaining, through calculation, a feature vector corresponding to each feature, obtaining a predicted score of the user for the target object based on values of N features and a feature vector corresponding to each of the N features, and recommending the target object to the user when the predicted score is greater than or equal to a preset threshold.
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14.发明授权公开(公告)号：US11334758B2
公开(公告)日：2022-05-17
申请号：US16729043
申请日：2019-12-27
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Ruiming Tang , Huifeng Guo , Zhenguo Li , Xiuqiang He
IPC: G06K9/62
Abstract: The method includes: obtaining a plurality of pieces of feature data; automatically performing two different types of nonlinear combination processing operations on the plurality of pieces of feature data to obtain two groups of processed data, where the two groups of processed data include a group of higher-order data and a group of lower-order data, the higher-order data is related to a nonlinear combination of m pieces of feature data in the plurality of pieces of feature data, and the lower-order data is related to a nonlinear combination of n pieces of feature data in the plurality of pieces of feature data, where m≥3, and m>n≥2; and determining prediction data based on a plurality of pieces of target data, where the plurality of pieces of target data include the two groups of processed data.
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公开(公告)号：US11281426B2
公开(公告)日：2022-03-22
申请号：US16455152
申请日：2019-06-27
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Bogdan Cautis , Ruiming Tang , Zhenhua Dong , Xiuqiang He , Zhirong Liu
IPC: G06F7/24 , G06F3/0482 , G06F17/18
Abstract: An application sorting method and apparatus are provided. The method includes: obtaining, a positive operation probability and positive operation feedback information of each of at least two data samples; calculating an uncertainty parameter of a positive operation probability of a first data sample based on the positive operation probabilities and the positive operation feedback information of the at least two data samples and feature indication information of at least one same feature in a plurality of features in the at least two data samples; and correcting the positive operation probability of the first data sample by using the uncertainty parameter of the positive operation probability; and sorting, based on corrected positive operation probabilities, application programs corresponding to the at least two data samples.
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Patent Agency Ranking
公开(公告)号：US20190366156A1
公开(公告)日：2019-12-05
申请号：US16540401
申请日：2019-08-14
Applicant: Huawei Technologies Co., Ltd.
Inventor： Ruiming Tang , Xiuqiang He , Zhenhua Dong , Zhirong Liu , Yanjie Li
Abstract: A route planning method includes obtaining exercise capability information of a wearer and one or more candidate routes, where the candidate routes include attribute features that comprise historical exercise capability information, where the historical exercise capability information is information calculated according to a first preset rule and based on obtained exercise capability information of a plurality of users having exercised along the candidate routes; determining a target route based on the attribute features of the candidate routes and the exercise capability information of the wearer; and outputting the target route information.
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公开(公告)号：US20250131269A1
公开(公告)日：2025-04-24
申请号：US19005088
申请日：2024-12-30
Applicant: Huawei Technologies Co., Ltd.
Inventor： Yichao Wang , Huifeng Guo , Zhenhua Dong , Ruiming Tang
IPC: G06N3/08 , G06F18/2132
Abstract: An operation prediction method includes obtaining a first embedding representation and a second embedding representation of attribute information of a user and an item respectively by using a first feature extraction network and a second feature extraction network. The first embedding representation indicates a feature unrelated to recommendation scenario information. The second embedding representation indicates a feature related to a target recommendation scenario. The first embedding representation and the second embedding representation are used for fusion to obtain a fused embedding representation. The operation prediction method further includes predicting target operation information of the user for the item based on the fused embedding representation.
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公开(公告)号：US12182141B2
公开(公告)日：2024-12-31
申请号：US18191704
申请日：2023-03-28
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Weiwen Liu , Yunjia Xi , Jianghao Lin , Ruiming Tang , Weinan Zhang , Yong Yu
IPC: G06F16/2457 , G06F16/248 , G06F40/103
Abstract: A system is provided for reranking. The system comprises a user device and one or more servers. The system is configured to receive a plurality of candidate lists, rerank the plurality of candidate lists based on page-level information and a format of a recommendation page, generate recommendation results based on the reranked lists, and send the recommendation results to the user device. Each candidate list comprises a plurality of candidate items. The page-level information comprises interactions between the candidate items in each candidate list and between different candidate lists among the plurality of candidate lists. The reranking comprises using the format of the recommendation page to determine pairwise item influences between candidate item pairs among the candidate items in the candidate lists. The user device is configured to display the recommendation page with the recommendation results from the one or more servers.
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公开(公告)号：US20240202491A1
公开(公告)日：2024-06-20
申请号：US18416924
申请日：2024-01-19
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Wei Guo , Jiarui Qin , Ruiming Tang , Zhirong Liu , Xiuqiang He , Weinan Zhang , Yong Yu
IPC: G06N3/04 , G06Q30/0601
CPC classification number: G06N3/04 , G06Q30/0631
Abstract: A recommendation device obtains to-be-predicted data and a plurality of target reference samples based on a similarity between the to-be-predicted data and the plurality of reference samples. Each reference sample and the to-be-predicted data each include user feature field data indicating a feature of a target user, and item feature field data indicating a feature of a target item. Each target reference sample and the to-be-predicted data have partially identical user feature field data and/or item feature field data. The recommendation device obtains target feature information of the to-be-predicted data based on the plurality of target reference samples and the to-be-predicted data. The recommendation device then uses the target feature information as input to a deep neural network to obtain a target item that is to be recommended.
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公开(公告)号：US11748452B2
公开(公告)日：2023-09-05
申请号：US17661448
申请日：2022-04-29
Applicant: Huawei Technologies Co., Ltd.
Inventor： Ruiming Tang , Huifeng Guo , Zhenguo Li , Xiuqiang He
IPC: G06F18/2321 , G06F18/2451 , G06F18/2133 , G06F18/2453
CPC classification number: G06F18/2321 , G06F18/2133 , G06F18/2451 , G06F18/2453
Abstract: The method includes: obtaining a plurality of pieces of feature data; automatically performing two different types of nonlinear combination processing operations on the plurality of pieces of feature data to obtain two groups of processed data, where the two groups of processed data include a group of higher-order data and a group of lower-order data, the higher-order data is related to a nonlinear combination of m pieces of feature data in the plurality of pieces of feature data, and the lower-order data is related to a nonlinear combination of n pieces of feature data in the plurality of pieces of feature data, where m≥3, and m>n≥2; and determining prediction data based on a plurality of pieces of target data, where the plurality of pieces of target data include the two groups of processed data.
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