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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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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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Patent Agency Ranking
公开(公告)号：US20190220749A1
公开(公告)日：2019-07-18
申请号：US16236570
申请日：2018-12-30
Inventor： Zhifan FENG , Chao LU , Yong ZHU , Ying LI
CPC classification number: G06N3/088 , G06F17/278 , G06F17/2785 , G06N3/0454 , G06N5/02 , G06N5/022 , G06N20/00
Abstract: The present disclosure provides a text processing method and device based on ambiguous entity words. The method includes: obtaining a context of a text to be disambiguated and at least two candidate entities represented by the text to be disambiguated; generating a semantic vector of the context based on a trained word vector model; generating a first entity vector of each of the at least two candidate entities based on a trained unsupervised neural network model; determining a similarity between the context and each candidate entity; and determining a target entity represented by the text to be disambiguated in the context.
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公开(公告)号：US20210216712A1
公开(公告)日：2021-07-15
申请号：US17149185
申请日：2021-01-14
Inventor： Shu WANG , Kexin REN , Xiaohan ZHANG , Zhifan FENG , Yang ZHANG , Yong ZHU
IPC: G06F40/279 , G06F17/16 , G06F17/18
Abstract: A method and an apparatus for labelling a core entity, and a related electronic device are proposed. A character vector sequence, a first word vector sequence and an entity vector sequence corresponding to a target text are obtained by performing character vector mapping, word vector mapping and entity vector mapping are performed on the target text, to obtain a target vector sequence corresponding to the target text. A first probability that each character of the target text is a starting character of a core entity and a second probability that each character of the target text is an ending character of a core entity are determined by encoding and decoding the target vector sequence. One or more core entities of the target text are determined based on the first probability and the second probability.
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公开(公告)号：US20200293905A1
公开(公告)日：2020-09-17
申请号：US16665882
申请日：2019-10-28
Inventor： Jianhui HUANG , Min QIAO , Zhifan FENG , Pingping HUANG , Yong ZHU , Yajuan LYU , Ying LI
Abstract: Embodiments of the present disclosure relate to a method and apparatus for generating a neural network. The method includes: acquiring a target neural network, the target neural network corresponding to a preset association relationship, and being configured to use two entity vectors corresponding to two entities in a target knowledge graph as an input, to determine whether an association relationship between the two entities corresponding to the inputted two entity vectors is the preset association relationship, the target neural network comprising a relational tensor predetermined for the preset association relationship; converting the relational tensor in the target neural network into a product of a target number of relationship matrices, and generating a candidate neural network comprising the target number of converted relationship matrices; and generating a resulting neural network using the candidate neural network.
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公开(公告)号：US20190220752A1
公开(公告)日：2019-07-18
申请号：US16213610
申请日：2018-12-07
Inventor： Ye XU , Zhifan FENG , Chao LU , Yang ZHANG , Zhou FANG , Shu WANG , Yong ZHU , Ying LI
IPC: G06N5/02 , G06N5/04 , G06N7/00 , G06F16/28 , G06F16/901 , G06F16/951 , G06F16/955 , G06F16/2458 , G06K9/62
CPC classification number: G06N5/022 , G06F16/2468 , G06F16/288 , G06F16/9024 , G06F16/951 , G06F16/955 , G06K9/6215 , G06K9/6276 , G06N5/04 , G06N7/005
Abstract: Embodiments of the disclosure disclose a method, apparatus, server, and storage medium for incorporating a structured entity, wherein the method for incorporating a structured entity can comprise: selecting a candidate entity associated with a to-be-incorporated structured entity from a knowledge graph, determining the to-be-incorporated structured entity being an associated entity based on prior attribute information of a category of the candidate entity and a preset model, merging the associated entity and the candidate entity, and incorporating the associated entity into the knowledge graph. The embodiments can select a candidate entity, and then integrate a preset model using prior knowledge, which can effectively improve the efficiency and accuracy in associating entities, and reduce the amount of calculation, to enable the structured entity to be simply and efficiently incorporated into the knowledge graph.
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公开(公告)号：US20210216715A1
公开(公告)日：2021-07-15
申请号：US17023915
申请日：2020-09-17
Inventor： Shu WANG , Kexin REN , Xiaohan ZHANG , Zhifan FENG , Yang ZHANG , Yong ZHU
IPC: G06F40/295 , G06F40/253 , G06F16/33 , G06N20/00 , G06N5/04
Abstract: A method for mining an entity focus in a text may include: performing word and phrase feature extraction on an input text; inputting an extracted word and phrase feature into a text coding network for coding, to obtain a coding sequence of the input text; processing the coding sequence of the input text using a core entity labeling network to predict a position of a core entity in the input text; extracting a subsequence corresponding to the core entity in the input text from the coding sequence of the input text, based on the position of the core entity in the input text; and predicting a position of a focus corresponding to the core entity in the input text using a focus labeling network, based on the coding sequence of the input text and the subsequence corresponding to the core entity in the input text.
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