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公开(公告)号：US11651164B2
公开(公告)日：2023-05-16
申请号：US17036609
申请日：2020-09-29
Inventor： Zhijie Liu , Qi Wang , Zhifan Feng , Zhou Fang , Chunguang Chai , Yong Zhu
IPC: G06F40/30 , G06F16/435 , G06F16/2458 , G06F40/253 , G06F40/279
CPC classification number: G06F40/30 , G06F16/2465 , G06F16/435 , G06F40/253 , G06F40/279 , G06F2216/03
Abstract: The present disclosure provides a method, a device, an equipment and a storage medium for mining a topic concept. The method includes: acquiring a plurality of candidate topic concepts based on a query; performing word segmentation on the plurality of candidate topic concepts and performing part-of-speech tagging on words obtained after performing the word segmentation, to obtain a part-of-speech sequence of each of the plurality of candidate topic concepts; and filtering the plurality of candidate topic concepts based on the part-of-speech sequence, to filter out a topic concept corresponding to a target part-of-speech sequence among the plurality of candidate topic concepts, in which a proportion of accurate topic concepts in the target part-of-speech sequence is lower than or equal to a first preset threshold, or a proportion of inaccurate topic concepts in the target part-of-speech sequence is higher than or equal to a second preset threshold.
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公开(公告)号：US11620532B2
公开(公告)日：2023-04-04
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：US20210326535A1
公开(公告)日：2021-10-21
申请号：US17036609
申请日：2020-09-29
Inventor： Zhijie Liu , Qi Wang , Zhifan Feng , Zhou Fang , Chunguang Chai , Yong Zhu
IPC: G06F40/30 , G06F40/253 , G06F40/279 , G06F16/2458 , G06F16/435
Abstract: The present disclosure provides a method, a device, an equipment and a storage medium for mining a topic concept. The method includes: acquiring a plurality of candidate topic concepts based on a query; performing word segmentation on the plurality of candidate topic concepts and performing part-of-speech tagging on words obtained after performing the word segmentation, to obtain a part-of-speech sequence of each of the plurality of candidate topic concepts; and filtering the plurality of candidate topic concepts based on the part-of-speech sequence, to filter out a topic concept corresponding to a target part-of-speech sequence among the plurality of candidate topic concepts, in which a proportion of accurate topic concepts in the target part-of-speech sequence is lower than or equal to a first preset threshold, or a proportion of inaccurate topic concepts in the target part-of-speech sequence is higher than or equal to a second preset threshold.
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公开(公告)号：US11727216B2
公开(公告)日：2023-08-15
申请号：US17117553
申请日：2020-12-10
Inventor： Zhijie Liu , Qi Wang , Zhifan Feng , Chunguang Chai , Yong Zhu
IPC: G06F17/00 , G06F40/30 , G06F40/295 , G06F17/16
CPC classification number: G06F40/30 , G06F17/16 , G06F40/295
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：US11490170B2
公开(公告)日：2022-11-01
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 , G06F16/783 , G06F16/78 , G06V40/16
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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Patent Agency Ranking
公开(公告)号：US20210216716A1
公开(公告)日：2021-07-15
申请号：US17213927
申请日：2021-03-26
Inventor： Qi Wang , Zhifan Feng , Zhijie Liu , Siqi Wang , Chunguang Chai , Yong Zhu
IPC: G06F40/295 , G06F16/33
Abstract: A method, apparatus, device, and storage medium for entity linking is disclosed. The method includes: acquiring a target text; determining at least one entity mention included in the target text; determining a candidate entity corresponding to each of the entity mention based on a preset knowledge base; determining a reference text of each of the candidate entity and determining additional feature information of each of the candidate entity; and determining an entity linking result based on the target text, each of the reference text, and each piece of the additional feature information.
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公开(公告)号：US11782981B2
公开(公告)日：2023-10-10
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: G06F16/901 , G06F16/28 , G06F16/951 , G06F16/955
CPC classification number: G06F16/9024 , G06F16/288 , G06F16/951 , G06F16/955
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：US11520812B2
公开(公告)日：2022-12-06
申请号：US16689862
申请日：2019-11-20
Inventor： Ye Xu , Zhifan Feng , Zhou Fang , Yang Zhang , Yong Zhu
IPC: G06F7/00 , G06F16/332 , G06K9/62 , G06N5/02 , G06V30/418
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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公开(公告)号：US11455542B2
公开(公告)日：2022-09-27
申请号：US16236570
申请日：2018-12-30
Inventor： Zhifan Feng , Chao Lu , Yong Zhu , Ying Li
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：US11995117B2
公开(公告)日：2024-05-28
申请号：US17069410
申请日：2020-10-13
Inventor： Qi Wang , Zhifan Feng , Zhijie Liu , Chunguang Chai , Yong Zhu
CPC classification number: G06F16/45
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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