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公开(公告)号：US20220198137A1
公开(公告)日：2022-06-23
申请号：US17382567
申请日：2021-07-22
Inventor： Jiawei LAI , Zhuobin DENG , Mengdi XU , Zhihong FU , Jingzhou HE
IPC: G06F40/194 , G06F40/40
Abstract: The present disclosure provides a text error-correcting method, apparatus, electronic device and readable storage medium and relates to the field of natural language processing and deep learning. In the present disclosure, an implementation solution employed when performing text error correction is: obtaining a text to be processed, and an error-correcting type of the text to be processed; selecting a target error-correcting model corresponding to the error-correcting type; processing the text to be processed using the target error-correcting model, and regarding a processing result as an error-correcting result of the text to be processed. The present disclosure can enhance the flexibility and accuracy of text error correction.
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公开(公告)号：US20210194977A1
公开(公告)日：2021-06-24
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.发明申请公开(公告)号：US20190095447A1
公开(公告)日：2019-03-28
申请号：US16054966
申请日：2018-08-03
Inventor： Qiugen XIAO , Jinbo ZHAN , Kunsheng ZHOU , Liqun ZHENG , Zhihong FU , Jingzhou HE
Abstract: Embodiments of the disclosure disclose a method, apparatus, device, and storage medium for establishing an error correction model based on an error correction platform. The method comprises: determining a target error correction level based on an error correction need of a user; and selecting at least one error correction module from each of at least two error correcting portions of the error correction platform based on the target error correction level, and combining the selected error correction module to form an error correction model.
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公开(公告)号：US20180365217A1
公开(公告)日：2018-12-20
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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15.发明申请公开(公告)号：US20210397901A1
公开(公告)日：2021-12-23
申请号：US17083704
申请日：2020-10-29
Inventor： Lihang LIU , Xiaomin FANG , Fan WANG , Jingzhou HE
IPC: G06K9/62 , G06N20/00 , G06F16/9535
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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Patent Agency Ranking
公开(公告)号：US20210383797A1
公开(公告)日：2021-12-09
申请号：US17411917
申请日：2021-08-25
Inventor： Fan WANG , Siqi BAO , Huang HE , Hua WU , Jingzhou HE , Haifeng WANG
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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17.发明申请公开(公告)号：US20210201198A1
公开(公告)日：2021-07-01
申请号：US16945183
申请日：2020-07-31
Inventor： Weibin LI , Zhifan ZHU , Weiyue SU , Jingzhou HE , Shikun FENG , Yuhui CAO , Xuyi CHEN , Danxiang ZHU
IPC: G06N20/00 , G06F16/901
Abstract: A method for generating node representations in a heterogeneous graph, an electronic device, and a non-transitory computer-readable storage medium, and relates to the field of machine learning technologies. The method includes: acquiring a heterogeneous graph; inputting the heterogeneous graph into a heterogeneous graph learning model to generate a node representation of each node in the heterogeneous graph, in which the heterogeneous graph learning model generates the node representation of each node by actions of: segmenting the heterogeneous graph into a plurality of subgraphs, in which each subgraph includes nodes of two types and an edge of one type between the nodes of two types; and generating the node representation of each node according to the plurality of subgraphs.
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公开(公告)号：US20210192288A1
公开(公告)日：2021-06-24
申请号：US16895242
申请日：2020-06-08
Inventor： Yuhui CAO , Shikun FENG , Xuyi CHEN , Jingzhou HE
Abstract: Embodiments of the present disclosure provide a method and apparatus for processing data. The method may include: acquiring a sample set; inputting a plurality of target samples in the sample set into a pre-trained first natural language processing model, respectively, to obtain prediction results output from the pre-trained first natural language processing model; determining the obtained prediction results as labels of the target samples in the plurality of target samples, respectively; and training a to-be-trained second natural language processing model, based on the plurality of target samples and the labels of the target samples to obtain a trained second natural language processing model, parameters in the first natural language processing model being more than parameters in the second natural language processing model.
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公开(公告)号：US20190057159A1
公开(公告)日：2019-02-21
申请号：US16054365
申请日：2018-08-03
Inventor： Chen LI , Di JIANG , Xinyu WANG , Yibin WEI , Pu WANG , Jingzhou HE
Abstract: Embodiments of the present disclosure disclose a method, an apparatus, a server, and a storage medium for recalling for a search. The method for recalling for a search includes: acquiring a search term inputted by a user; calculating a semantic vector of the search term using a pre-trained neural network model; and recalling, according to a pre-established index, target documents related to the semantic vector of the search term from candidate documents, the index being established based on the semantic vectors of the candidate documents, and the semantic vectors of the candidate documents being calculated using the pre-trained neural network model. The embodiments of the present disclosure may solve a problem in the existing method for recalling that the recalling accuracy is affected by failing to generalize semantics, to improve the accuracy of recalling for a search.
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20.发明申请公开(公告)号：US20180365208A1
公开(公告)日：2018-12-20
申请号：US15934496
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 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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