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公开(公告)号：US20230115737A1
公开(公告)日：2023-04-13
申请号：US18080432
申请日：2022-12-13
Inventor： Shuai CHEN , Qi WANG , Zhifan FENG , Chunguang CHAI , Yong ZHU
IPC: G06F16/483 , G06F16/43 , G06F18/25 , G06F18/22 , G06N5/02
Abstract: A method of processing multimedia data, a device, and a medium, which relates to a field of an artificial intelligence technology, in particular to fields of knowledge graph and deep learning. The method of processing the multimedia data includes: recognizing the multimedia data so as to obtain at least one key information of the multimedia data; querying a predetermined knowledge base according to the at least one key information, so as to determine a multimedia name associated with the at least one key information and an association degree between the multimedia name and the at least one key information; and determining, in the multimedia name, a name of the multimedia data based on a similarity between alternative multimedia data for the multimedia name and the multimedia data, in response to the association degree being less than a first threshold value.
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公开(公告)号：US20220284218A1
公开(公告)日：2022-09-08
申请号：US17502173
申请日：2021-10-15
Inventor： Hu YANG , Feng HE , Qi WANG , Zhifan FENG , Chunguang CHAI , Yong ZHU
Abstract: The present disclosure discloses a video classification method, an electronic device and a storage medium, and relates to the field of computer technologies, and particularly to the field of artificial intelligence technologies, such as knowledge graph technologies, computer vision technologies, deep learning technologies, or the like. The video classification method includes: extracting a keyword in a video according to multi-modal information of the video; acquiring background knowledge corresponding to the keyword, and determining a text to be recognized according to the keyword and the background knowledge; and classifying the text to be recognized to obtain a class of the video.
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公开(公告)号：US20230010160A1
公开(公告)日：2023-01-12
申请号：US17945415
申请日：2022-09-15
Inventor： Shuai CHEN , Qi WANG , Hu YANG , Feng HE , Zhifan FENG , Chunguang CHAI , Yong ZHU
Abstract: Disclosed are a method for processing multimodal data using a neural network, a device, and a medium, and relates to the field of artificial intelligence and, in particular to multimodal data processing, video classification, and deep learning. The neural network includes: an input subnetwork configured to receive the multimodal data to output respective first features of a plurality of modalities; a plurality of cross-modal feature subnetworks, each of which is configured to receive respective first features of two corresponding modalities to output a cross-modal feature corresponding to the two modalities; a plurality of cross-modal fusion subnetworks, each of which is configured to receive at least one cross-modal feature corresponding to a corresponding target modality and other modalities to output a second feature of the target modality; and an output subnetwork configured to receive respective second features of the plurality of modalities to output a processing result of the multimodal data.
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4.发明公开公开(公告)号：US20230153337A1
公开(公告)日：2023-05-18
申请号：US18157452
申请日：2023-01-20
Inventor： Wenbin JIANG , Yajuan LV , Chunguang CHAI , Yong ZHU
IPC: G06F16/332 , G06F40/30
CPC classification number: G06F16/3329 , G06F40/30
Abstract: A question answering method, a method of training a question answering model, a device, and a medium are provided, which relate to a field of artificial intelligence technology, in particular to fields of natural language processing technology, deep learning technology, and knowledge mapping technology. The question answering method includes: obtaining data to be processed, wherein the data to be processed includes a question and candidate answers; performing general semantic understanding on the data to be processed to obtain a general data feature; selecting a target question answering mode from candidate question answering modes based on the general data feature; and processing the general data feature by using the target question answering mode, to obtain a target answer for the question from the candidate answers.
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公开(公告)号：US20220350965A1
公开(公告)日：2022-11-03
申请号：US17864636
申请日：2022-07-14
Inventor： Tongyang LIU , Shu WANG , Wanli CHANG , Wei ZHENG , Zhifan FENG , Chunguang CHAI , Yong ZHU
IPC: G06F40/211 , G06F40/30 , G06F40/109 , G06N3/08
Abstract: A method for generating a pre-trained language model, includes: obtaining sample files; obtaining typography structure information and text information of the sample files by parsing the sample files; obtaining a plurality of task models of a pre-trained language model; obtaining a trained pre-trained language model by jointly training the pre-trained language model and the plurality of task models according to the typography structure information and the text information; and generating a target pre-trained language model by fine-tuning the trained pre-trained language model according to the typography structure information and the text information.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20210397980A1
公开(公告)日：2021-12-23
申请号：US17036160
申请日：2020-09-29
IPC: G06N5/02 , G06N5/04 , G06F40/279 , G06K9/62
Abstract: The present disclosure provides an information recommendation method, which relates to a field of knowledge graph. The method includes: acquiring request information; extracting a request entity word representing an entity from the request information; determining recommendation information based on the request entity word and a pre-constructed knowledge graph; and pushing the recommendation information, wherein the knowledge graph is constructed based on a text, and the knowledge graph indicates a first word representing a source of the text. The present disclosure further provides an information recommendation apparatus, an electronic device and a computer-readable storage medium.
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7.发明申请公开(公告)号：US20230092736A1
公开(公告)日：2023-03-23
申请号：US17872318
申请日：2022-07-25
Inventor： Wenbin JIANG , Yajuan LYU , Yong ZHU , Hua WU , Haifeng WANG
Abstract: The present disclosure provides a method for processing intelligent question-answering, an intelligent question-answering system, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies, such as machine learning technologies, natural language processing technologies, or the like. An implementation includes: acquiring an input question and input data information; and based on the question, the data information and a plurality of knowledge bases, deciding an answer to the question by multilayer appreciation using a plurality of understanding module layers.
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公开(公告)号：US20230086145A1
公开(公告)日：2023-03-23
申请号：US17936761
申请日：2022-09-29
Inventor： Wenbin JIANG , Yajuan LV , Yong ZHU , Hua WU , Haifeng WANG
IPC: G06F16/738 , G06N5/02
Abstract: A method of processing data, a device, and a medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision, natural language technology, speech technology, deep learning and knowledge graph. The method of processing data includes: generating a video feature, a question feature and an answer feature based on acquired video data, acquired question data and acquired candidate answer data; determining a link relationship between the video feature, the question feature and the answer feature; and determining a matching result for the video data, the question data and the candidate answer data based on the link relationship.
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公开(公告)号：US20230018489A1
公开(公告)日：2023-01-19
申请号：US17862519
申请日：2022-07-12
Inventor： Wenbin JIANG , Yajuan LYU , Yong ZHU , Hua WU , Haifeng WANG
IPC: G06F16/242 , G06F16/21 , G06F16/245 , G06N5/02
Abstract: The present disclosure discloses a method for acquiring a structured question-answering (QA) model, a QA method and corresponding apparatuses, and relates to knowledge graph and deep learning technologies in the field of artificial intelligence technologies. A specific implementation solution involves: acquiring training samples corresponding to N structured QA database types, the training samples including question samples, information of the structured QA database types and query instruction samples used by the question samples to query structured QA databases of the types, N being an integer greater than 1; and training a text generation model by using the training samples to obtain the structured QA model, wherein the question samples and the information of the structured QA database types are taken as input to the text generation model, and the query instruction samples are taken as target output of the text generation model.
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10.发明申请公开(公告)号：US20210263974A1
公开(公告)日：2021-08-26
申请号：US17173318
申请日：2021-02-11
Inventor： Qian LI , Yabing SHI , Ye JIANG , Chunguang CHAI , Yong ZHU
IPC: G06F16/9032 , G06N3/04 , G06F16/906 , G06F16/903 , G06F40/30
Abstract: Provided by the present disclosure is a new category tag mining method, involving the field of knowledge graph technology, and including: obtaining a plurality of queries during a current preset time period; labeling a category tag on each query of the plurality of queries, by using a pre-trained sequence labeling model, to extract the category tag currently corresponding to the query from the query; and removing a category tag already existing in a preset current category tag library from category tags currently corresponding to all the queries, and determining a remaining category tag as a new category tag. The present disclosure also provides an electronic device and a non-transitory computer-readable storage medium.
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