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公开(公告)号:US11734392B2
公开(公告)日:2023-08-22
申请号:US17237978
申请日:2021-04-22
Inventor: Yang Xue , Fan Wang , Jingzhou He
CPC classification number: G06F18/40 , G06F18/2132 , G06F18/253 , G06F40/30 , G06T7/251 , G06V20/46 , G06T2207/20084
Abstract: An active interaction method, an electronic device and a readable storage medium, relating to the field of deep learning and image processing technologies, are disclosed. According to an embodiment, the active interaction method includes: acquiring a video shot in real time; extracting a visual target from each image frame of the video, and generating a first feature vector of each visual target; for each image frame of the video, fusing the first feature vector of each visual target and identification information of the image frame to which the visual target belongs to generate a second feature vector of each visual target; aggregating the second feature vectors with the same identification information respectively to generate a third feature vector corresponding to each image frame; and initiating active interaction in response to determining that the active interaction is to be performed according to the third feature vector of a preset image frame.
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公开(公告)号:US10831993B2
公开(公告)日:2020-11-10
申请号:US16306488
申请日:2016-12-22
Inventor: Kunsheng Zhou , Jingzhou He , Lei Shi , Shikun Feng
IPC: G06F40/242 , G06F16/00 , G06F40/30 , G06N3/02 , G06F40/20 , G06F40/284 , G06F17/18 , G06N3/08
Abstract: Disclosed are a method and an apparatus for constructing a binary feature dictionary. The method may include: extracting binary features from a corpus; calculating a preset statistic of each binary feature; and selecting a preset number of binary features in sequence according to the preset statistic to constitute the binary feature dictionary.
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公开(公告)号:US20180144024A1
公开(公告)日:2018-05-24
申请号:US15677612
申请日:2017-08-15
Inventor: Zhihong Fu , Zengfeng Zeng , Qiugen Xiao , Jingzhou He , Lei Shi , Pengkai Li
CPC classification number: G06F16/243 , G06F16/2453 , G06F16/951 , G06F17/2705 , G06F17/273 , G06N5/048
Abstract: A method and an apparatus for correcting a query based on artificial intelligence, including: receiving a first query input by a user, and judging whether the first query satisfies an error correcting condition according to a preset error correcting strategy; determining a first segment to be corrected in the first query if the first query satisfies the error correcting condition; acquiring one or more first candidate results corresponding to the first segment according to a preset candidate recalling strategy; determining an error correcting result corresponding to the first segment according to quality feature values of the one or more first candidate results; and performing an error correction on the first query according to the error correcting result, and generating a second query.
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公开(公告)号:US11977850B2
公开(公告)日:2024-05-07
申请号:US17411917
申请日:2021-08-25
Inventor: Fan Wang , Siqi Bao , Huang He , Hua Wu , Jingzhou He , Haifeng Wang
CPC classification number: G06F40/35 , G06F16/325 , G06F16/3347 , G06F18/285 , G06F40/30 , G10L15/01 , G10L15/18 , G10L15/22
Abstract: A method for dialogue processing, an electronic device and a storage medium are provided. The specific technical solution includes: obtaining a dialogue history; selecting a target machine from a plurality of machines; inputting the dialogue history into a trained dialogue model in the target machine to generate a response to the dialogue history, in which the dialogue model comprises a common parameter and a specific parameter, and different machines correspond to the same common parameter.
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5.
公开(公告)号:US11836222B2
公开(公告)日:2023-12-05
申请号:US17083704
申请日:2020-10-29
Inventor: Lihang Liu , Xiaomin Fang , Fan Wang , Jingzhou He
IPC: G06Q30/00 , G06F18/21 , G06N20/00 , G06F16/9535 , G06Q30/0207 , G05B19/418 , G06Q30/0601
CPC classification number: G06F18/2178 , G06F16/9535 , G06F18/2193 , G06N20/00 , G06Q30/0221 , G06Q30/0225 , G06Q30/0631
Abstract: A method and apparatus for optimizing a recommendation system, a device and a computer storage medium are described, which relates to the technical field of deep learning and intelligent search in artificial intelligence. A specific implementation solution is: taking the recommendation system as an agent, a user as an environment, each recommended content of the recommendation system as an action of the agent, and a long-term behavioral revenue of the user as a reward of the environment; and optimizing to-be-optimized parameters in the recommendation system by reinforcement learning to maximize the reward of the environment. The present disclosure can effectively optimize long-term behavioral revenues of users.
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6.
公开(公告)号:US20180365227A1
公开(公告)日:2018-12-20
申请号:US15941065
申请日:2018-03-30
Inventor: Liqun Zheng , Jinbo Zhan , Qiugen Xiao , Zhihong Fu , Jingzhou He , Guyue Zhou
IPC: G06F17/27
Abstract: Embodiments of the present disclosure disclose a method and an apparatus for customizing a word segmentation model based on artificial intelligence, a device and a medium. The method includes the followings. A customized segmentation training corpus is acquired. A first preset word segmentation model is rectified with an increment training method or a weight intervention method, based on the customized segmentation training corpus, to obtain a customized word segmentation model corresponding to the customized segmentation training corpus.
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公开(公告)号:US20220019847A1
公开(公告)日:2022-01-20
申请号:US17237978
申请日:2021-04-22
Inventor: Yang Xue , Fan Wang , Jingzhou He
Abstract: An active interaction method, an electronic device and a readable storage medium, relating to the field of deep learning and image processing technologies, are disclosed. According to an embodiment, the active interaction method includes: acquiring a video shot in real time; extracting a visual target from each image frame of the video, and generating a first feature vector of each visual target; for each image frame of the video, fusing the first feature vector of each visual target and identification information of the image frame to which the visual target belongs to generate a second feature vector of each visual target; aggregating the second feature vectors with the same identification information respectively to generate a third feature vector corresponding to each image frame; and initiating active interaction in response to determining that the active interaction is to be performed according to the third feature vector of a preset image frame.
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公开(公告)号:US10929390B2
公开(公告)日:2021-02-23
申请号:US15677612
申请日:2017-08-15
Inventor: Zhihong Fu , Zengfeng Zeng , Qiugen Xiao , Jingzhou He , Lei Shi , Pengkai Li
IPC: G06F15/16 , G06F16/242 , G06N5/04 , G06F16/951 , G06F16/2453 , G06F40/205 , G06F40/232
Abstract: A method and an apparatus for correcting a query based on artificial intelligence, including: receiving a first query input by a user, and judging whether the first query satisfies an error correcting condition according to a preset error correcting strategy; determining a first segment to be corrected in the first query if the first query satisfies the error correcting condition; acquiring one or more first candidate results corresponding to the first segment according to a preset candidate recalling strategy; determining an error correcting result corresponding to the first segment according to quality feature values of the one or more first candidate results; and performing an error correction on the first query according to the error correcting result, and generating a second query.
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公开(公告)号:US10650096B2
公开(公告)日:2020-05-12
申请号:US15934410
申请日:2018-03-23
Inventor: Liqun Zheng , Jinbo Zhan , Qiugen Xiao , Zhihong Fu , Jingzhou He , Guyue Zhou
Abstract: Embodiments of the present disclosure disclose a word segmentation method based on artificial intelligence, a server and a storage medium. The word segmentation method may include: acquiring a corpus to be segmented and a segmentation model corresponding to a preset segmentation template; matching the corpus to be segmented with the segmentation model according to a preset matching algorithm, and acquiring a target phrase satisfying a first preset rule in the corpus to be segmented; modifying an emission matrix corresponding to the segmentation model and the corpus to be segmented according to the target phrase; and performing a word segmentation on the corpus to be segmented according to the emission matrix modified, to acquire a first segmentation result.
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公开(公告)号:US10606949B2
公开(公告)日:2020-03-31
申请号:US15921386
申请日:2018-03-14
Inventor: Zhifan Zhu , Shikun Feng , Kunsheng Zhou , Jingzhou He
Abstract: This disclosure discloses an artificial intelligence based method and apparatus for checking a text. An embodiment of the method comprises: lexing a first to-be-checked text and a second to-be-checked text respectively, determining word vectors of the lexed words to generate a first word vector sequence and a second word vector sequence; inputting the first word vector sequence and the second word vector sequence respectively into a pre-trained convolutional neural network containing at least one multi-scale convolutional layer, identifying vector sequences in a plurality of vector sequences outputted by a last multi-scale convolutional layer as eigenvector sequences, to obtain eigenvector sequence groups respectively corresponding to the texts; combining eigenvector sequences in each eigenvector sequence group to generate a combined eigenvector sequence; and analyzing the generated combined eigenvector sequences to determine whether the first text and the second text pass a similarity check. The embodiment improves the flexibility in checking a text.
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