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公开(公告)号：US11586814B2
公开(公告)日：2023-02-21
申请号：US16856450
申请日：2020-04-23
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xin Jiang , Lifeng Shang , Hang Li , Zichao Li
IPC: G06F40/289 , G06F40/237
Abstract: A paraphrase sentence generation method and apparatus relating to the research field of natural language processing include generating m second sentences based on a first sentence and a paraphrase generation model, determining a matching degree between each of the m second sentences and the first sentence based on a paraphrase matching model, and determining n second sentences from the m second sentences based on matching degrees among the m second sentences and the first sentence, where the paraphrase generation model is obtained through reinforcement learning-based training based on a reward of the paraphrase matching model.
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Patent Agency Ranking
公开(公告)号：US20250139359A1
公开(公告)日：2025-05-01
申请号：US18943845
申请日：2024-11-11
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Yichun Yin , Lifeng Shang , Xin Jiang , Xiao Chen
IPC: G06F40/216 , G06F40/166 , G06F40/279 , G06F40/30 , G06N3/045 , G06N3/084
Abstract: A text processing model training method, and a text processing method and apparatus in the natural language processing field in the artificial intelligence field are disclosed. The training method includes: obtaining training text; separately inputting the training text into a teacher model and a student model to obtain sample data output by the teacher model and prediction data output by the student model; the sample data includes a sample semantic feature and a sample label; the prediction data includes a prediction semantic feature and a prediction label; and the teacher model is a pre-trained language model used for text classification; and training a model parameter of the student model based on the sample data and the prediction data, to obtain a target student model. The method enables the student model to effectively perform knowledge transfer, thereby improving accuracy of a text processing result of the student model.
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公开(公告)号：US12204590B2
公开(公告)日：2025-01-21
申请号：US16868970
申请日：2020-05-07
Applicant: Huawei Technologies Co., Ltd.
Inventor： Zhefeng Yan , Lifeng Shang , Tao Cai , Li Qian
IPC: G06F16/9035 , G06F9/48
Abstract: An information processing method includes receiving first request information entered by a user, determining a first task engine for the first request information, where a first slot is set in the first task engine, extracting key information from the first request information based on the first slot, and if the key information fails to be extracted from the first request information based on the first slot, or if the key information is extracted from the first request information based on the first slot, but the extracted key information does not meet a condition, obtaining target key information from a shared parameter list of the user.
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公开(公告)号：US12073334B2
公开(公告)日：2024-08-27
申请号：US17577713
申请日：2022-01-18
Applicant: Huawei Technologies Co., Ltd.
Inventor： Lifeng Shang , Zhengdong Lu , Hang Li
CPC classification number: G06N5/043 , G06F16/3329 , G06F16/3344 , G06F40/35 , G10L13/08 , G10L15/22 , H04L51/02 , G10L2015/225 , G10L2015/228
Abstract: A method includes: obtaining a text entered by a user; determining at least one topic related to the text; determining a target dialogue robot from the plurality of dialogue robots based on the at least one topic related to the text and a predefined mapping relationship between a dialogue robot and a topic, where a target topic corresponding to the target dialogue robot is some or all of the at least one topic related to the text; allocating the text to the target dialogue robot; and obtaining a reply for the text from the target dialogue robot, where the reply is generated by the target dialogue robot based on at least one semantic understanding of the text.
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公开(公告)号：US20190341021A1
公开(公告)日：2019-11-07
申请号：US16514683
申请日：2019-07-17
Applicant: Huawei Technologies Co., Ltd.
Inventor： Lifeng Shang , Zhengdong Lu , Hang Li
IPC: G10L13/08 , G06F17/27 , G10L15/22 , G06N5/04 , G06F16/332
Abstract: An apparatus is pre-equipped with a plurality of dialogue robots, and each dialogue robot is configured to conduct a human-computer dialogue based on at least one topic. The method includes: obtaining a text entered by a user; determining at least one topic related to the text, and determining a target dialogue robot from the plurality of dialogue robots based on the at least one topic related to the text and a predefined mapping relationship between a dialogue robot and a topic, where a target topic corresponding to the target dialogue robot is some or all of the at least one topic related to the text; and allocating the text to the target dialogue robot and obtaining a reply for the text from the target dialogue robot, where the reply is generated by the target dialogue robot based on at least one semantic understanding of the text.
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公开(公告)号：US20170034111A1
公开(公告)日：2017-02-02
申请号：US15223836
申请日：2016-07-29
Applicant: Huawei Technologies Co., Ltd.
Inventor： Lifeng Shang , Jing Li , KamFai Wong
IPC: H04L12/58
Abstract: A method and apparatus for determining key social information, comprises acquiring directly-retransmitted social information and indirectly-retransmitted social information of original social information, and establishing a social information retransmitting tree; acquiring an information characteristic of each piece of retransmitted social information in the social information retransmitting tree; determining a characteristic vector of each piece of retransmitted social information according to the information characteristic of the retransmitted social information; inputting the obtained characteristic vector into a preset filtering model, and acquiring candidate key social information; and selecting final key social information from all candidate key social information according to a criticality evaluation value of each piece of candidate key social information. In the technical solution of the present disclosure, directly-retransmitted social information and indirectly-retransmitted social information are comprehensively considered, and key social information is selected from all retransmitted social information of original social information, which improves accuracy of a selection result.
Abstract translation: 一种用于确定关键社交信息的方法和装置，包括获取直接重传的社交信息和间接重传的原始社交信息的社会信息，以及建立社交信息重传树; 在社交信息重传树中获取每条重发社会信息的信息特征; 根据重发的社会信息的信息特征，确定每条重发社会信息的特征向量; 将所获得的特征向量输入到预设过滤模型中，并获取候选关键社会信息; 根据每个候选关键社会信息的临界评价值，从所有候选关键社会信息中选择最终关键社会信息。 在本公开的技术方案中，全面地考虑直接重传的社会信息和间接重传的社会信息，并且从所有重传的原始社交信息的社会信息中选择关键的社会信息，这提高了选择结果的准确性。
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