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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：US20160110649A1
公开(公告)日：2016-04-21
申请号：US14977991
申请日：2015-12-22
Applicant: Huawei Technologies Co., Ltd.
Inventor： Zhenhua Dong , Xiuqiang He , Gong Zhang , Guoxiang Cao
CPC classification number: G06N5/046 , G06F16/24575 , G06F16/9535 , G06N20/00 , H04W4/50
Abstract: An application program recommending method may include acquiring current context information of the terminal, acquiring an amount of context information generated when the terminal runs a first application program, where the first application program refers to an application program stored in the terminal, determining a to-be-used recommending mechanism according to the amount of the context information generated when the terminal runs the first application program, and determining, according to the to-be-used recommending mechanism, a second application program corresponding to the current context information, where the second application program refers to a to-be-recommended application program; and displaying the second application program. In this way, accuracy of predicting an application program to be used by a user is improved. Moreover, when historical information of using an application program by the user is insufficient, a to-be-recommended application program can also be accurately determined.
Abstract translation: 应用程序推荐方法可以包括获取终端的当前上下文信息，获取当终端运行第一应用程序时产生的上下文信息的量，其中第一应用程序参考存储在终端中的应用程序， 根据当终端运行第一应用程序时生成的上下文信息的量，根据所使用的推荐机制确定与当前上下文信息相对应的第二应用程序，其中， 第二个应用程序是指一个要推荐的应用程序; 并显示第二应用程序。 以这种方式，提高了用户使用的预测应用程序的精度。 此外，当使用用户的应用程序的历史信息不足时，还可以准确地确定要推荐的应用程序。
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公开(公告)号：US20150211872A1
公开(公告)日：2015-07-30
申请号：US14584338
申请日：2014-12-29
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Jianmin WANG , Fang You , Chingman Au Yeung , Xiaojuan Ma , Xiuqiang He
IPC: G01C21/34
CPC classification number: G08G1/096791 , G01C21/3691 , G08G1/0968
Abstract: Embodiments of the present invention disclose a navigation method and a navigation device, which are used to exchange information between different motorists, so that the navigation device can keep abreast of a latest road condition. The method in the embodiments of the present invention includes: acquiring a first destination of a first navigation device; determining a second navigation device, where a distance between a second destination of the second navigation device and the first destination of the first navigation device is less than a first preset distance; and establishing a communication connection between the first navigation device and the second navigation device. In the embodiments of the present invention, different navigation devices can exchange information with each other, so that the navigation devices can keep abreast of the latest road condition.
Abstract translation: 本发明的实施例公开了用于在不同驾驶者之间交换信息的导航方法和导航装置，使得导航装置可以跟上最新的道路状况。 本发明实施例中的方法包括：获取第一导航装置的第一目的地; 确定第二导航装置，其中第二导航装置的第二目的地与第一导航装置的第一目的地之间的距离小于第一预设距离; 以及在所述第一导航装置和所述第二导航装置之间建立通信连接。 在本发明的实施例中，不同的导航装置可以彼此交换信息，使得导航装置可以跟上最新的道路状况。
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公开(公告)号：US12210577B2
公开(公告)日：2025-01-28
申请号：US17989719
申请日：2022-11-18
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Guohao Cai , Gang Wang , Zhenhua Dong , Xiaoguang Li , Xiuqiang He , Hong Zhu
IPC: G06F16/00 , G06F16/9535 , G06F16/954
Abstract: A method and an apparatus for training a search recommendation model, and a method and an apparatus for sorting search results are provided. The training method includes: obtaining a training sample set including a sample user behavior group sequence and a masked sample user behavior group sequence; and using the training sample set as input data, and training a search recommendation model, to obtain a trained search recommendation model, where a target of the training is to obtain the object of the response operation of the sample user after the mask processing, the search recommendation model is used to predict a label of a candidate recommendation object in search results corresponding to a query field when a target user inputs the query field, and the label is used to indicate a probability that the target user performs a response operation on the candidate recommendation object.
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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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Patent Agency Ranking
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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公开(公告)号：US11580457B2
公开(公告)日：2023-02-14
申请号：US16863110
申请日：2020-04-30
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Fei Chen , Zhenhua Dong , Zhenguo Li , Xiuqiang He , Li Qian , Shuaihua Peng
Abstract: Example prediction methods and apparatus are described. One example includes sending a first model parameter and a second model parameter by a server to a plurality of terminals. The first model parameter and the second model parameter are adapted to a prediction model of the terminal. The server receives a first prediction loss sent by at least one of the plurality of terminals. A first prediction loss sent by each of the at least one terminal is calculated by the terminal based on the prediction model that uses the first model parameter and the second model parameter. The server updates the first model parameter based on the first prediction loss sent by the at least one terminal to obtain an updated first model parameter. The server updates the second model parameter based on the first prediction loss sent by the at least one terminal to obtain an updated second model parameter.
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公开(公告)号：US20230031522A1
公开(公告)日：2023-02-02
申请号：US17964117
申请日：2022-10-12
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Bin Liu , Ruiming Tang , Huifeng Guo , Niannan Xue , Guilin Li , Xiuqiang He , Zhenguo Li
Abstract: This application relates to the field of artificial intelligence. A recommendation method based on automatic feature grouping includes: obtaining a plurality of candidate recommended objects and a plurality of association features of each of the plurality of candidate recommended objects; performing multi-order automatic feature grouping on the plurality of association features of each candidate recommended object, to obtain a multi-order feature interaction set of each candidate recommended object; obtaining an interaction feature contribution value of each candidate recommended object through calculation based on the plurality of association features in the multi-order feature interaction set of each candidate recommended object; obtaining a prediction score of each candidate recommended object through calculation based on the interaction feature contribution value of each candidate recommended object; and determining one or more corresponding candidate recommended objects with a high prediction score as a target recommended object.
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公开(公告)号：US09984304B2
公开(公告)日：2018-05-29
申请号：US14925368
申请日：2015-10-28
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xiuqiang He , Gong Zhang
CPC classification number: G06K9/46 , G06F17/30259 , G06F17/30525 , G06K9/00335 , G06K9/52 , G06K9/64 , G06K9/6807 , G06T2207/20224 , G06T2207/30232
Abstract: The present invention discloses a method and system for recognizing a user activity type, where the method includes: collecting an image of a location in which a user is located; extracting, from the image, characteristic data of an environment in which the user is located and characteristic data of the user; and obtaining, by recognition, an activity type of the user by using an image recognition model related to an activity type or an image library related to an activity type and the characteristic data.
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公开(公告)号：US20160048738A1
公开(公告)日：2016-02-18
申请号：US14925368
申请日：2015-10-28
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xiuqiang He , Gong Zhang
CPC classification number: G06K9/46 , G06F17/30259 , G06F17/30525 , G06K9/00335 , G06K9/52 , G06K9/64 , G06K9/6807 , G06T2207/20224 , G06T2207/30232
Abstract: The present invention discloses a method and system for recognizing a user activity type, where the method includes: collecting an image of a location in which a user is located; extracting, from the image, characteristic data of an environment in which the user is located and characteristic data of the user; and obtaining, by recognition, an activity type of the user by using an image recognition model related to an activity type or an image library related to an activity type and the characteristic data.
Abstract translation: 本发明公开了一种用于识别用户活动类型的方法和系统，其中该方法包括：收集用户所在位置的图像; 从图像中提取用户所在的环境的特征数据和用户的特征数据; 并且通过使用与活动类型相关的图像识别模型或与活动类型相关的图像库和特征数据，通过识别获得用户的活动类型。
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