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公开(公告)号：US12140441B2
公开(公告)日：2024-11-12
申请号：US17531529
申请日：2021-11-19
Inventor： Weijia Zhang , Hao Liu , Dejing Dou , Hui Xiong
IPC: G01C21/34 , G06N20/00 , G06Q30/0601 , H04L67/12
Abstract: A method for recommending a station for a vehicle, a device, and a storage medium are provided. The method comprises: receiving, by a server, an access request from a vehicle; obtaining, based on the access request, a plurality of observation values from a plurality of stations associated with the vehicle, respectively, each observation value is based on a corresponding pre-trained recommendation model, each observation value includes factors associated with access of the vehicle to the station corresponding to the observation value; determining, an action value for the station based on the observation value and the pre-trained recommendation model for the station, the action value for the station indicates a matching degree between the access request and the station; determining a recommended station among the plurality of stations based on the action values of the plurality of stations; and sending to the vehicle an instruction of driving to the recommended station.
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公开(公告)号：US11829447B2
公开(公告)日：2023-11-28
申请号：US17173142
申请日：2021-02-10
Inventor： Xinjiang Lu , Nengjun Zhu , Hui Xiong
IPC: G06F17/18 , G06F18/2323 , G06N3/02 , G06F18/25
CPC classification number: G06F18/2323 , G06F17/18 , G06F18/25 , G06N3/02
Abstract: This disclosure discloses a resident area prediction method, apparatus, device and storage medium, involving artificial intelligence technology, big data, deep learning and multi-task learning. The specific implementation plan is: acquiring a resident area data of a target user, and the resident area data including the resident area of the target user and the corresponding resident time; obtaining an association relationship between the resident areas of the target user by inputting the resident area data into an area relationship model, and the area relationship model is used to reflect a position relationship between the areas; determining a time-sequence relationship between the areas visited by the target user, according to the association relationship, the resident time and the visiting POI data; predicting a target resident area of the target user, according to the time-sequence relationship and the basic attribute information of the target user.
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Patent Agency Ranking
公开(公告)号：US20230093528A1
公开(公告)日：2023-03-23
申请号：US18070775
申请日：2022-11-29
Inventor： Ying SUN , Hengshu Zhu , Chuan Qin , Fuzhen Zhuang , Hui Xiong
Abstract: An interpretation method for a neural network model is provided. Input data and output data corresponding to the input data of a neural network model are acquired, in which the neural network model includes layers of networks connected sequentially, and each layer of network corresponds to a plurality of candidate concepts. A key inference path through which the output data is obtained by the neural network model based on the input data are acquired, in which the key inference path includes target concepts respectively used by the layers of networks when the input data is processed in the neural network model, in which the target concepts are selected from the plurality of candidate concepts. Interpretation information corresponding to the layers of networks is determined according to the target concepts corresponding to the layers of networks, respectively. The key inference path and the interpretation information are output.
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公开(公告)号：US20220414689A1
公开(公告)日：2022-12-29
申请号：US17900649
申请日：2022-08-31
Inventor： Qi Zhang , Hengshu Zhu , Peng Wang , Hao Liu , Hui Xiong
Abstract: A method and an apparatus for training a path representation model are provided. The method may include: acquiring at least one trajectory point of at least one user, where each trajectory point of each user includes a place passed by the user, a start time and a duration; inputting the at least one trajectory point of the at least one user into a pre-trained model to obtain a trajectory representation of each user; obtaining, for each user, a position of each trajectory point from the trajectory representation of the user by searching according to the start time and the duration of each trajectory point of the user; and adjusting a network parameter of the pre-trained model according to a difference between the place passed by each user and the position of each trajectory point obtained by searching, to obtain a path representation model.
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公开(公告)号：US20230127699A1
公开(公告)日：2023-04-27
申请号：US18088872
申请日：2022-12-27
Inventor： Ji Liu , Sunjie Yu , Weijia Zhang , Hao Liu , Hengshu Zhu , Dejing Dou , Hui Xiong
Abstract: A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.
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公开(公告)号：US11740102B2
公开(公告)日：2023-08-29
申请号：US16864648
申请日：2020-05-01
Inventor： Xinjiang Lu , Yanyan Li , Jianguo Duan , Hui Xiong , Guanglei Du
CPC classification number: G01C21/3682
Abstract: The present disclosure discloses a method, an apparatus, a device, and a storage medium for determining a point of interest area, and relates to the field of automatic driving. The implementation solution is that the method is applied to an electronic device, and includes: receiving a point of interest area determination request input by a first user, the point of interest area determination request including a target area coverage; and acquiring grid data of at least one block within the target area coverage in response to the point of interest area determination request; acquiring, for each block, positioning data of a second user within each preset time period and number of parent points of interest; clustering corresponding grid data according to the positioning data, the grid data and the number of the parent points of interest; determining at least one POI area in each block according to a clustering result.
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公开(公告)号：US11442930B2
公开(公告)日：2022-09-13
申请号：US17021001
申请日：2020-09-15
Inventor： Yanyan Li , Jianguo Duan , Hui Xiong
IPC: G06F16/23 , G06F16/215 , G06Q30/02
Abstract: The present application discloses a method for data aggregation, the method includes: acquiring original data to be aggregated and dividing the original data into at least one first data set; determining whether each of the at least one first data set has a corresponding historical aggregation record; when there is at least one second data set with a historical aggregation record in the at least one first data set, acquiring a historical aggregation result corresponding to each second data set to obtain at least one first aggregation result; performing aggregation on each third data set without a historical aggregation record to obtain at least one second aggregation result; and determining a third aggregation result of the original data according to the at least one first aggregation result and the at least one second aggregation result, and determining a data tag of the original data according to the third aggregation result.
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