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公开(公告)号:US20210216717A1
公开(公告)日:2021-07-15
申请号:US17213940
申请日:2021-03-26
Inventor: Shu Wang , Kexin Ren , Xiaohan Zhang , Zhifan Feng , Chunguang Chai , Yong Zhu
IPC: G06F40/295 , G06K9/00 , G06F40/30 , G06N3/08 , G06F16/33
Abstract: A method, electronic device and storage medium for generating information are disclosed. The method includes: acquiring a plurality of tag entity words from a target video, the tag entity words including a person entity word, a work entity word, a video category entity word, and a video core entity word, the video core entity word including an entity word for characterizing a content related to the target video; linking, for a tag entity word among the plurality of tag entity words, the tag entity word to a node of a preset knowledge graph; determining semantic information of the target video based on a linking result of each of the tag entity words; and structuring the semantic information of the target video based on a relationship between the node and an edge of the knowledge graph, to obtain structured semantic information of the target video.
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公开(公告)号:US11995560B2
公开(公告)日:2024-05-28
申请号:US17043227
申请日:2020-04-07
Inventor: Quan Wang , Pingping Huang , Haifeng Wang , Wenbin Jiang , Yajuan Lyu , Yong Zhu , Hua Wu
IPC: G06N5/02 , G06F16/31 , G06F16/33 , G06F16/35 , G06F16/36 , G06F16/901 , G06F16/906 , G06F40/279 , G06N3/042 , G06N3/045 , G06N3/08 , G06N5/022
CPC classification number: G06N5/02 , G06N5/022 , G06F16/31 , G06F16/316 , G06F16/3347 , G06F16/35 , G06F16/36 , G06F16/367 , G06F16/9017 , G06F16/9024 , G06F16/906 , G06F40/279 , G06N3/042 , G06N3/045 , G06N3/08
Abstract: The present disclosure discloses a method and an apparatus for generating a vector representation of a knowledge graph, and relates to a field of a field of artificial intelligence technologies. The detailed implementing solution is: obtaining a knowledge graph, the knowledge graph including a plurality of entity nodes; obtaining a context type and context data corresponding to the knowledge graph; and generating vector representations corresponding to the plurality of entity nodes by a context model based on the context data and the context type.
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公开(公告)号:US11900269B2
公开(公告)日:2024-02-13
申请号:US16677464
申请日:2019-11-07
Inventor: Weiyu Wang , Chao Lu , Yong Zhu
CPC classification number: G06N5/025 , G06F16/26 , G06F16/288
Abstract: Exemplary embodiments of the present disclosure provide a method and apparatus for managing a knowledge base, a device and a computer readable storage medium. The method for managing a knowledge base includes: forking, in response to receiving a request for modification of a rule for a first namespace, the rule to the first namespace, the rule being used to constrain structured data in a knowledge base; modifying, based on the request for modification of the rule, the rule in the first namespace; and adding the modified rule to a rule base associated with the knowledge base.
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公开(公告)号:US11847164B2
公开(公告)日:2023-12-19
申请号:US17213940
申请日:2021-03-26
Inventor: Shu Wang , Kexin Ren , Xiaohan Zhang , Zhifan Feng , Chunguang Chai , Yong Zhu
IPC: G06F17/00 , G06F16/78 , G06F16/33 , G06F40/295 , G06F40/30 , G06N3/08 , G06V20/40 , G06V40/16 , G06V10/764 , G06V10/82
CPC classification number: G06F16/78 , G06F16/3344 , G06F40/295 , G06F40/30 , G06N3/08 , G06V10/764 , G06V10/82 , G06V20/46 , G06V20/48 , G06V40/172
Abstract: A method, electronic device and storage medium for generating information are disclosed. The method includes: acquiring a plurality of tag entity words from a target video, the tag entity words including a person entity word, a work entity word, a video category entity word, and a video core entity word, the video core entity word including an entity word for characterizing a content related to the target video; linking, for a tag entity word among the plurality of tag entity words, the tag entity word to a node of a preset knowledge graph; determining semantic information of the target video based on a linking result of each of the tag entity words; and structuring the semantic information of the target video based on a relationship between the node and an edge of the knowledge graph, to obtain structured semantic information of the target video.
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公开(公告)号:US11775761B2
公开(公告)日:2023-10-03
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 , G06F16/33 , G06N20/00 , G06F40/253 , G06N5/04 , G06F40/30
CPC classification number: G06F40/295 , G06F16/3347 , G06F40/253 , G06N5/04 , G06N20/00 , G06F40/30 , G06F2216/03
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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公开(公告)号:US11557120B2
公开(公告)日:2023-01-17
申请号:US17350731
申请日:2021-06-17
Inventor: Qi Wang , Zhifan Feng , Hu Yang , Feng He , Chunguang Chai , Yong Zhu
IPC: G06V20/40 , G06V40/16 , G06V10/426 , G06K9/62 , G06V30/10
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:US11361002B2
公开(公告)日:2022-06-14
申请号:US17249001
申请日:2021-02-17
Inventor: Yabing Shi , Shuangjie Li , Ye Jiang , Yang Zhang , Yong Zhu
IPC: G06F16/28 , G06F40/295 , G06F40/30 , G06N20/00
Abstract: The disclosure discloses a method and an apparatus for recognizing an entity word. The method includes: obtaining an entity word category and a document to be recognized; generating an entity word question based on the entity word category; segmenting the document to be recognized to generate a plurality of candidate sentences; inputting the entity word question and the plurality of candidate sentences into a question-answer model trained in advance to obtain an entity word recognizing result; and obtaining an entity word set corresponding to the entity word question based on the entity word recognizing result.
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公开(公告)号:US20220004892A1
公开(公告)日:2022-01-06
申请号:US17480575
申请日:2021-09-21
Inventor: Quan Wang , Haifeng Wang , Yajuan Lyu , Yong Zhu
IPC: G06N5/02 , G06N20/00 , G06F40/30 , G06F40/205
Abstract: A method for training a multivariate relationship generation model, an electronic device and a medium are provided. The technical solution includes: obtaining a plurality of knowledge text entries; performing semantic parsing on each knowledge text entry to obtain a plurality of entities and semantic information of each knowledge text entry; constructing a heterogeneous graph based on the plurality of entities and the semantic information; and training an initial artificial intelligence (AI) network model based on the heterogeneous graph to obtain a multivariate relationship generation model.
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公开(公告)号:US20200242140A1
公开(公告)日:2020-07-30
申请号:US16689862
申请日:2019-11-20
Inventor: Ye Xu , Zhifan Feng , Zhou Fang , Yang Zhang , Yong Zhu
IPC: G06F16/332 , G06N5/02 , G06K9/62 , G06K9/00
Abstract: Embodiments of the present disclosure provide a method, apparatus, device and medium for determining text relevance. The method for determining text relevance may include: identifying, from a predefined knowledge base, a first set of knowledge elements associated with a first text and a second set of knowledge elements associated with a second text. The knowledge base includes a knowledge representation consist of knowledge elements. The method may further include: determining knowledge element relevance between the first set of knowledge elements and the second set of knowledge elements, and determining text relevance between the second text and the first text based at least on the knowledge element relevance.
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