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11.发明授权公开(公告)号：US11443100B2
公开(公告)日：2022-09-13
申请号：US16950975
申请日：2020-11-18
Inventor： Mengdi Xu , Zhuobin Deng , Jiawei Lai , Zhihong Fu , Jingzhou He
IPC: G06F40/00 , G06F40/166 , G06N20/00 , G06F40/20 , G06K9/62
Abstract: A method and apparatus for correcting character errors, an electronic device and a storage medium are disclosed, which relates to the natural language processing field and the deep learning field. The method may include: for a character to be processed, acquiring the score of each character in a pre-constructed vocabulary, the score being a score of the reasonability of the character in the vocabulary at the position of the character to be processed; selecting top K characters as candidates of the character to be processed, K being a positive integer greater than one; selecting an optimal candidate from the K candidates; and replacing the character to be processed with the optimal candidate if the optimal candidate is different from the character to be processed. With the solution of the present application, the accuracy of an error correction result, or the like, may be improved.
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公开(公告)号：US11412070B2
公开(公告)日：2022-08-09
申请号：US16891822
申请日：2020-06-03
Inventor： Xiaomin Fang , Yaxue Chen , Lihang Liu , Lingke Zeng , Fan Wang , Jingzhou He
Abstract: Embodiment of the disclosure provide a method and apparatus for generating information. The method includes: acquiring vectors of a plurality of users, the vector being used to characterize behavior habits of the users; inputting the vectors of the plurality of users and push information pushed by a push system to the plurality of users into a feedback information generating model established in advance, to generate the feedback information of the plurality of users for the push information, wherein the feedback information generating model is used to characterize a corresponding relationship between the vectors, the push information and the feedback information; and generating an evaluation report of the push system based on the feedback information.
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13.发明授权公开(公告)号：US10664659B2
公开(公告)日：2020-05-26
申请号：US15934496
申请日：2018-03-23
Inventor： Liqun Zheng , Jinbo Zhan , Qiugen Xiao , Zhihong Fu , Jingzhou He , Guyue Zhou
IPC: G06F40/284 , G06N3/08 , G06N3/04 , G06F40/242
Abstract: Embodiments of the present disclosure disclose a method for modifying a segmentation model based on artificial intelligence, a device and a storage medium. The method may include: acquiring a model parameter of the segmentation model, and performing a training on a feature vector corresponding to a preset generalized feature of a first training corpus via a neural network so as to acquire a model parameter of the preset generalized feature; performing a word segmentation on the first training corpus according to the model parameter of the segmentation model and the model parameter of the preset generalized feature, so as to acquire a segmentation result; and comparing the segmentation result with the first training corpus according to a preset rule, and modifying the model parameter of the segmentation model and a parameter of the neural network according to a comparison result.
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公开(公告)号：US10650102B2
公开(公告)日：2020-05-12
申请号：US15900166
申请日：2018-02-20
Inventor： Pengkai Li , Jingzhou He , Zhihong Fu , Xianwei Xin
Abstract: The present disclosure discloses a method and apparatus for generating a parallel text in the same language. The method comprises: acquiring a source segmented word sequence and a pre-trained word vector table; determining a source word vector sequence corresponding to the source segmented word sequence, according to the word vector table; importing the source word vector sequence into a first pre-trained recurrent neural network model, to generate an intermediate vector of a preset dimension for characterizing semantics of the source segmented word sequence; importing the intermediate vector into a second pre-trained recurrent neural network model, to generate a target word vector sequence corresponding to the intermediate vector; and determining a target segmented word sequence corresponding to the target word vector sequence according to the word vector table, and determining the target segmented word sequence as a parallel text in the same language corresponding to the source segmented word sequence.
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公开(公告)号：US20180365231A1
公开(公告)日：2018-12-20
申请号：US15900166
申请日：2018-02-20
Inventor： Pengkai Li , Jingzhou He , Zhihong Fu , Xianwei Xin
Abstract: The present disclosure discloses a method and apparatus for generating a parallel text in the same language. The method comprises: acquiring a source segmented word sequence and a pre-trained word vector table; determining a source word vector sequence corresponding to the source segmented word sequence, according to the word vector table; importing the source word vector sequence into a first pre-trained recurrent neural network model, to generate an intermediate vector of a preset dimension for characterizing semantics of the source segmented word sequence;importing the intermediate vector into a second pre-trained recurrent neural network model, to generate a target word vector sequence corresponding to the intermediate vector; and determining a target segmented word sequence corresponding to the target word vector sequence according to the word vector table, and determining the target segmented word sequence as a parallel text in the same language corresponding to the source segmented word sequence.
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Patent Agency Ranking
公开(公告)号：US20180349781A1
公开(公告)日：2018-12-06
申请号：US15954015
申请日：2018-04-16
Inventor： Zhihui Liu , Wei Bi , Yuhui Cao , Jingzhou He , Di Jiang
Abstract: Embodiments of the present disclosure disclose a method and a device for judging news quality based on AI and a storage medium. The method includes: constructing a news quality classification model based on a news feature of known high-quality news and/or a news feature of known low-quality news; and judging news quality of news to be detected with the news quality classification model.
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公开(公告)号：US12260327B2
公开(公告)日：2025-03-25
申请号：US17210141
申请日：2021-03-23
Inventor： Xiaomin Fang , Fan Wang , Yelan Mo , Jingzhou He
Abstract: The present application discloses an optimizer learning method and apparatus, an electronic device and a readable storage medium, which relates to the field of deep learning technologies. An implementation solution adopted by the present application during optimizer learning is: acquiring training data, the training data including a plurality of data sets each including neural network attribute information, neural network optimizer information, and optimizer parameter information; and training a meta-learning model by taking the neural network attribute information and the neural network optimizer information in the data sets as input and taking the optimizer parameter information in the data sets as output, until the meta-learning model converges. The present application can implement self-adaptation of optimizers, so as to improve generalization capability of the optimizers.
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公开(公告)号：US11954449B2
公开(公告)日：2024-04-09
申请号：US17475073
申请日：2021-09-14
Inventor： Fan Wang , Siqi Bao , Xinxian Huang , Hua Wu , Jingzhou He
IPC: G06F40/40 , G06F16/33 , G06F16/332 , G06N7/01 , G10L15/22
CPC classification number: G06F40/40 , G06F16/3329 , G06F16/3344 , G06N7/01 , G10L15/22
Abstract: The disclosure discloses a method for generating a conversation, an electronic device, and a storage medium. The detailed implementation includes: obtaining a current conversation and historical conversations of the current conversation; selecting multiple reference historical conversations from the historical conversations and adding the multiple reference historical conversations to a temporary conversation set; and generating reply information of the current conversation based on the current conversation and the temporary conversation set.
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公开(公告)号：US11537798B2
公开(公告)日：2022-12-27
申请号：US16895297
申请日：2020-06-08
Inventor： Siqi Bao , Huang He , Junkun Chen , Fan Wang , Hua Wu , Jingzhou He
IPC: G06F40/30 , G06F16/332
Abstract: Embodiments of the present disclosure relate to a method and apparatus for generating a dialogue model. The method may include: acquiring a corpus sample set, a corpus sample including input information and target response information; classifying corpus samples in the corpus sample set, setting discrete hidden variables for the corpus samples based on a classification result to generate a training sample set, a training sample including the input information, the target response information, and a discrete hidden variable; and training a preset neural network using the training sample set to obtain the dialogue model, the dialogue model being used to represent a corresponding relationship between inputted input information and outputted target response information.
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公开(公告)号：US20220004867A1
公开(公告)日：2022-01-06
申请号：US17210141
申请日：2021-03-23
Inventor： Xiaomin Fang , Fan Wang , Yelan Mo , Jingzhou He
Abstract: The present application discloses an optimizer learning method and apparatus, an electronic device and a readable storage medium, which relates to the field of deep learning technologies. An implementation solution adopted by the present application during optimizer learning is: acquiring training data, the training data including a plurality of data sets each including neural network attribute information, neural network optimizer information, and optimizer parameter information; and training a meta-learning model by taking the neural network attribute information and the neural network optimizer information in the data sets as input and taking the optimizer parameter information in the data sets as output, until the meta-learning model converges. The present application can implement self-adaptation of optimizers, so as to improve generalization capability of the optimizers.
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