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公开(公告)号：US11709893B2
公开(公告)日：2023-07-25
申请号：US16685731
申请日：2019-11-15
Inventor： Yan Chen , Kai Liu , Jing Liu , Yajuan Lyu , Qiaoqiao She , Kun Liu
IPC: G06F16/90 , G06F16/9032 , G06N3/02 , G06F16/9538 , G06F16/903 , G06F16/906
CPC classification number: G06F16/90332 , G06F16/906 , G06F16/90324 , G06F16/90335 , G06F16/9538 , G06N3/02
Abstract: The present disclosure provides a search method, an electronic device and a storage medium, and belongs to a technical field of the Internet. The method includes: determining a first set of features corresponding to an original search statement by parsing the original search statement; obtaining each initial search result corresponding to the original search statement; determining a second set of features corresponding to an initial search result by parsing a title of the initial search result; determining a rewritten search statement corresponding to the original search statement and the initial search result by codecing the first set of features and the second set of features; and obtaining a supplementary search result corresponding to the rewritten search statement.
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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：US10810272B2
公开(公告)日：2020-10-20
申请号：US15349919
申请日：2016-11-11
Inventor： Kai Liu , Yang Feng , Qin Yang , Yajuan Lyu
IPC: G06F16/9535 , G06F16/35 , G06N5/04 , G06F16/638 , G06F16/2458
Abstract: The present disclosure provides a method and an apparatus for broadcasting a search result based on artificial intelligence. The method includes: receiving a query sentence inputted by a user, and acquiring a plurality of candidate search results according to the query sentence; analyzing each candidate search result to determine a category of each candidate search result, in which the category includes a structured result and a rich-text result; acquiring intention information of the query sentence, and screening the plurality of candidate search results according to the intention information and the category of each candidate search result to obtain a screened search result; and generating text information corresponding to the screened search result, and broadcasting the text information.
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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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5.发明申请
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：US11216504B2
公开(公告)日：2022-01-04
申请号：US16705749
申请日：2019-12-06
Inventor： Guocheng Niu , Bolei He , Chengxiang Liu , Xinyan Xiao , Yajuan Lyu
IPC: G06F16/36 , G06F40/30 , G06F40/295 , G06N3/08
Abstract: A document recommendation method based on a semantic tag and a document recommendation device. The method includes: for each document, acquiring a first candidate tag set corresponding to the document, and processing each first candidate tag in the first candidate tag set corresponding to the document to obtain a second candidate tag set corresponding to the document; performing normalization processing on each second candidate tag in the second candidate tag set corresponding to the document to obtain a third candidate tag set corresponding to the document; performing expanding process on each third candidate tag in the third candidate tag set corresponding to the document, and acquiring a fourth candidate tag set corresponding to the document, to form a document library having semantic tags; and recommending a target document obtained from the document library having semantic tags to the user, according to historical semantic tag.
