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公开(公告)号：US20240330310A1
公开(公告)日：2024-10-03
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
CPC classification number: G06F16/24578 , 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：US20210256403A1
公开(公告)日：2021-08-19
申请号：US17313383
申请日：2021-05-06
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Ruiming Tang , Qing Liu , Yuzhou Zhang , Li Qian , Haokun Chen , Weinan Zhang , Yong Yu
Abstract: In a recommendation-providing method in the field of artificial intelligence, an apparatus for generating recommendations obtains a recommendation system status parameter based on a plurality of historical recommended objects and a user behavior for each historical recommended object, such as clicks or downloads. The apparatus determines a target set among lower-level sets according to the recommendation system status parameter and a selection policy corresponding to an upper-level set, where the lower-level sets and upper-level set correspond to nodes on a clustering tree representing available to-be-presented objects, and each set corresponds to one selection policy. The apparatus then determines a target to-be-recommended object from the to-be recommended objects in the target set.
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公开(公告)号：US10709934B2
公开(公告)日：2020-07-14
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：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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5.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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Patent Agency Ranking
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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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：US11830033B2
公开(公告)日：2023-11-28
申请号：US16198704
申请日：2018-11-21
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Zhirong Liu , Ruiming Tang , Zhenhua Dong , Xiuqiang He , Guoxiang Cao
IPC: G06Q30/02 , G06Q30/06 , G06F16/28 , G06Q30/0251 , G06Q30/0601
CPC classification number: G06Q30/0255 , G06F16/285 , G06Q30/0251 , G06Q30/0631
Abstract: The method includes: collecting historical operations of sample users for M items, and predicting a preference value of a target user for each of the M items according to historical operations of the sample users for each of the M items, collecting classification data of N to-be-recommended items, and classifying the N to-be-recommended items according to the classification data of the N to-be-recommended items, to obtain X themes, where each of the X themes includes at least one of the N to-be-recommended items, and the N to-be-recommended items are some or all of the M items; calculating a preference value of the target user for each of the X themes according to a preference value of the target user for a to-be-recommended item included in each of the X themes; and pushing a target theme to the target user.
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公开(公告)号：US11734716B2
公开(公告)日：2023-08-22
申请号：US16198704
申请日：2018-11-21
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Zhirong Liu , Ruiming Tang , Zhenhua Dong , Xiuqiang He , Guoxiang Cao
IPC: G06Q30/02 , G06Q30/06 , G06F16/28 , G06Q30/0251 , G06Q30/0601
CPC classification number: G06Q30/0255 , G06F16/285 , G06Q30/0251 , G06Q30/0631
Abstract: The method includes: collecting historical operations of sample users for M items, and predicting a preference value of a target user for each of the M items according to historical operations of the sample users for each of the M items, collecting classification data of N to-be-recommended items, and classifying the N to-be-recommended items according to the classification data of the N to-be-recommended items, to obtain X themes, where each of the X themes includes at least one of the N to-be-recommended items, and the N to-be-recommended items are some or all of the M items; calculating a preference value of the target user for each of the X themes according to a preference value of the target user for a to-be-recommended item included in each of the X themes; and pushing a target theme to the target user.
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10.发明授权公开(公告)号：US11531867B2
公开(公告)日：2022-12-20
申请号：US16850549
申请日：2020-04-16
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Ruiming Tang , Minzhe Niu , Yanru Qu , Weinan Zhang , Yong Yu
Abstract: Example user behavior prediction methods and apparatus are described. One example method includes obtaining a first contribution value of each piece of characteristic data for a specified behavior after obtaining behavior prediction information including a plurality of pieces of characteristic data. Every N pieces of characteristic data in the plurality of pieces of characteristic data may be processed by using one corresponding characteristic interaction model, to obtain a second contribution value of the every N pieces of characteristic data for the specified behavior. Finally, an execution probability of executing the specified behavior by a user may be determined based on the obtained first contribution value and the obtained second contribution value, to predict a user behavior. In the example method, interaction impact of the plurality of pieces of characteristic data on the specified behavior is considered during behavior prediction.
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