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公开(公告)号：US20220237388A1
公开(公告)日：2022-07-28
申请号：US17714891
申请日：2022-04-06
Inventor： Xinjiang LU , Yanyan LI , Jingbo ZHOU , Dejing DOU
IPC: G06F40/40 , G06F40/30 , G06F40/177 , G06F40/20
Abstract: A method and apparatus for generating a table description text, a device, and a storage medium are provided. An implementation of the method includes: acquiring a to-be-described table, and analyzing the to-be-described table to obtain a set of metalanguage of the to-be-described table, and finally generating a description text of the to-be-described table based on the metalanguage in the set of metalanguage.
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2.发明申请公开(公告)号：US20220130495A1
公开(公告)日：2022-04-28
申请号：US17570505
申请日：2022-01-07
Inventor： Shuangli LI , Jingbo ZHOU , Liang HUANG , Haoyi XIONG , Fan WANG , Tong XU , Hui XIONG , Dejing DOU
Abstract: A method for determining correlation between a drug and a target, and an electronic device are provided. The method includes: establishing a spatial molecular graph of a candidate drug and the target, the spatial molecular graph including an atomic node set and an edge set, the atomic node set including atoms in the candidate drug and atoms in the target, the edge set including at least one atom connection edge; inputting a first atom feature of the atomic node set and the spatial molecular graph into a first GAT for prediction, to obtain a second atom feature of the atomic node set; and determining a parameter value of the correlation between the candidate drug and the target in accordance with the second atom feature of the atomic node set.
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公开(公告)号：US20250110255A1
公开(公告)日：2025-04-03
申请号：US18957351
申请日：2024-11-22
Inventor： Jingbo ZHOU , Pengfei REN
IPC: G01W1/00 , G06F40/166
Abstract: A method of determining meteorological information, an electronic device and a storage medium are provided, which relate to a field of artificial intelligence technology, and in particular to fields of deep learning and large models. The method includes performing a feature extraction on meteorological raster data of a target region within a target time period to obtain a meteorological feature vector; inputting to-be-processed meteorological data of the target region within the target time period into a large language model to obtain a text summary including a meteorological information determination manner; performing an information enhancement processing on the meteorological feature vector by using the text summary to obtain an information enhancement result; and performing a self-attention processing on the information enhancement result to obtain a meteorological information determination result output for the to-be-processed meteorological data.
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公开(公告)号：US20240371259A1
公开(公告)日：2024-11-07
申请号：US18393376
申请日：2023-12-21
Inventor： Yixiong XIAO , Hao YUAN , Jingbo ZHOU
IPC: G08G1/01
Abstract: Provided is a source tracing method for traffic congestion, an electronic device and a storage medium, relating to the field of smart transportation, traffic management, traffic information processing and other technologies. The method includes: determining an undetermined road section and at least two reference road sections related to the undetermined road section from a target road network; obtaining a congestion infection distance between the undetermined road section and the reference road section within a target period; calculating a congestion time difference between a first congestion moment of the undetermined road section within the target period and a second congestion moment of the reference road section within the target period; and determining the undetermined road section as a congestion source of the target road network within the target period when determining that a correlation between the congestion infection distance and the congestion time difference meets a preset correlation requirement.
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公开(公告)号：US20240370719A1
公开(公告)日：2024-11-07
申请号：US18512766
申请日：2023-11-17
Inventor： Congxi XIAO , Jizhou HUANG , Jingbo ZHOU
Abstract: This disclosure provides a data generation method, model training method, electronic device, and medium. The data generation method includes: obtaining urban graph data, the urban graph data including a node set, an edge set and a feature set, wherein the node set includes a central node corresponding to a predetermined urban entity, the edge set includes a neighborhood corresponding to the central node, the neighborhood includes other nodes in the node set connected to the central node via an edge, and the feature set includes features of nodes in the node set; partitioning a target region into at least two sub-regions to obtain a region partition set; obtaining a regional feature of each sub-region by aggregating features corresponding to all nodes in the sub-region; and updating a feature of the central node based on the regional features of the sub-regions in the region partition set to obtain target feature data.
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Patent Agency Ranking
公开(公告)号：US20240273297A1
公开(公告)日：2024-08-15
申请号：US18642593
申请日：2024-04-22
Inventor： Yu LI , Jiawei ZHENG , Xinjiang LU , Hongwei XIE , Xuejiao LIN , Jingbo ZHOU
IPC: G06F40/295
CPC classification number: G06F40/295
Abstract: An entity recognition method, a model training method, an electronic device, and a medium, which relate to fields of artificial intelligence, information acquiring technologies. The entity recognition method includes: extracting specified entities from a text in a source file of a webpage to be recognized, and acquiring a text encoding result for each specified entity; determining a text block formed by each specified entity in the webpage, and encoding a relative layout information between each two text blocks, to obtain a position encoding result; constructing a triple by the position encoding result for each two text blocks and the text encoding results for respective specified entities of the two text blocks; and performing a graph convolution on each triple to obtain a relation recognition result for the webpage to be recognized, where the relation recognition result indicates whether an association exists between each two text blocks in the webpage.
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7.发明申请公开(公告)号：US20220374776A1
公开(公告)日：2022-11-24
申请号：US17868113
申请日：2022-07-19
Inventor： Ji LIU , Beichen MA , Chendi ZHOU , Jingbo ZHOU , Ruipu ZHOU , Dejing DOU
IPC: G06N20/00
Abstract: The present disclosure provides a method and apparatus for federated learning, which relate to the technical fields such as big data and deep learning. A specific implementation is: generating, for each task in a plurality of different tasks trained simultaneously, a global model for each task; receiving resource information of each available terminal in a current available terminal set; selecting a target terminal corresponding to each task from the current available terminal set, based on the resource information and the global model; and training the global model using the target terminal until a trained global model for each task meets a preset condition.
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公开(公告)号：US20220374775A1
公开(公告)日：2022-11-24
申请号：US17867516
申请日：2022-07-18
Inventor： Ji LIU , Beichen MA , Jingbo ZHOU , Ruipu ZHOU , Dejing DOU
Abstract: A method for multi-task scheduling, a device and a storage medium are provided. The method may include: initializing a list of candidate scheduling schemes, the candidate scheduling scheme being used to allocate a terminal device for training to each machine learning task in a plurality of machine learning tasks; perturbing, for each candidate scheduling scheme in the list of candidate scheduling schemes, the candidate scheduling scheme to generate a new scheduling scheme; determining whether to replace the candidate scheduling scheme with the new scheduling scheme based on a fitness value of the candidate scheduling scheme and a fitness value of the new scheduling scheme, to generate a new scheduling scheme list; and determining a target scheduling scheme, based on the fitness value of each new scheduling scheme in the new scheduling scheme list.
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公开(公告)号：US20220237474A1
公开(公告)日：2022-07-28
申请号：US17721659
申请日：2022-04-15
Inventor： Yanyan LI , Jingbo ZHOU , Jizhou HUANG , Dejing DOU
IPC: G06N5/02 , G06F16/901
Abstract: A method and apparatus for semanticization is provided. The method includes: ascertaining a target coordinate of a to-be-semanticized location; ascertaining, through a pre-built regional spatial index tree, a target region to which the target coordinate of the to-be-semanticized location belongs; and ascertaining semantic information of the to-be-semanticized location based on semantic information of the target region.
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公开(公告)号：US20250139369A1
公开(公告)日：2025-05-01
申请号：US18956107
申请日：2024-11-22
Inventor： Jingbo ZHOU , Congxi XIAO , Yixiong XIAO , Jizhou HUANG
IPC: G06F40/284 , G06N20/00
Abstract: A method is provided that includes: obtaining first urban data of a first sample urban region; inputting the first urban data into a multi-modal foundation model to obtain respective predicted vector representations of a plurality of first data segments; obtaining a plurality of general-purpose foundation models that are pre-trained; for each general-purpose foundation model: generating a vector representation label of a first data segment of a corresponding data modality by using the general-purpose foundation model; and determining a knowledge distillation loss of the general-purpose foundation model based on the vector representation label and a predicted vector representation of the first data segment; and adjusting parameters of the multi-modal foundation model based on at least respective knowledge distillation losses of the plurality of general-purpose foundation models.
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