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Patent Agency Ranking
公开(公告)号：US20210250666A1
公开(公告)日：2021-08-12
申请号：US17243055
申请日：2021-04-28
Inventor： Hu YANG , Shu WANG , Xiaohan ZHANG , Qi WANG , Zhifan FENG , Chunguang CHAI
IPC: H04N21/845 , G06F16/78 , G06F16/783 , G06K9/00
Abstract: The disclosure provides a method for processing a video, an electronic device, and a computer storage medium. The method includes: determining a plurality of first identifiers related to a first object based on a plurality of frames including the first object in a target video; determining a plurality of attribute values associated with the plurality of first identifiers based on a knowledge base related to the first object; determining a set of frames from the plurality of frames, in which one or more attribute values associated with one or more first identifiers determined from each one of the set of frames are predetermined values; and splitting the target video into a plurality of video clips based on positions of the set of frames in the plurality of frames.
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公开(公告)号：US20210216580A1
公开(公告)日：2021-07-15
申请号：US17147092
申请日：2021-01-12
Inventor： Zhijie LIU , Qi WANG , Zhifan FENG , Yang ZHANG , Yong ZHU
Abstract: A method and an apparatus for generating a text topic and an electronic device are disclosed. The method includes: obtaining entities included in a text to be processed by mining the entities; determining each candidate entity in a knowledge graph corresponding to each entity included in the text to be processed through entity links; determining a set of core entities corresponding to the text to be processed by clustering candidate entities; determining each candidate topic included in the text to be processed based on a matching degree between each keyword in the text to be processed and each reference topic in a preset topic graph; and obtaining the text topic from the set of core entities and the candidate topics based on association between each core entity and the text to be processed as well as association between each candidate topic and the text to be processed.
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公开(公告)号：US20210383069A1
公开(公告)日：2021-12-09
申请号：US17117553
申请日：2020-12-10
Inventor： Zhijie LIU , Qi WANG , Zhifan FENG , Chunguang CHAI , Yong ZHU
IPC: G06F40/30 , G06F40/295 , G06F17/16
Abstract: A method, apparatus, device, and storage medium for linking an entity, relates to the technical fields of knowledge graph and deep learning are provided. The method may include: acquiring a target text; determining at least one entity mention included in the target text and a candidate entity corresponding to each entity mention; determining an embedding vector of each candidate entity based on the each candidate entity and a preset entity embedding vector determination model; determining context semantic information of the target text based on the target text and each embedding vector; determining type information of the at least one entity mention; and determining an entity linking result of the at least one entity mention, based on the each embedding vector, the context semantic information, and each type information.
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公开(公告)号：US20210256051A1
公开(公告)日：2021-08-19
申请号：US17069410
申请日：2020-10-13
Inventor： Qi WANG , Zhifan FENG , Zhijie LIU , Chunguang CHAI , Yong ZHU
Abstract: A theme classification method based on multimodality is related to a field of a knowledge map. The method includes obtaining text information and non-text information of an object to be classified. The non-text information includes at least one of visual information and audio information. The method also includes determining an entity set of the text information based on a pre-established knowledge base, and then extracting a text feature of the object based on the text information and the entity set. The method also includes determining a theme classification of the object based on the text feature and a non-text feature of the object.
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公开(公告)号：US20220036085A1
公开(公告)日：2022-02-03
申请号：US17350731
申请日：2021-06-17
Inventor： Qi WANG , Zhifan FENG , Hu YANG , Feng HE , Chunguang CHAI , Yong ZHU
Abstract: Technical solutions for video event recognition relate to the fields of knowledge graphs, deep learning and computer vision. A video event graph is constructed, and each event in the video event graph includes: M argument roles of the event and respective arguments of the argument roles, with M being a positive integer greater than one. For a to-be-recognized video, respective arguments of the M argument roles of a to-be-recognized event corresponding to the video are acquired. According to the arguments acquired, an event is selected from the video event graph as a recognized event corresponding to the video.
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