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公开(公告)号：US20200293921A1
公开(公告)日：2020-09-17
申请号：US16750304
申请日：2020-01-23
Inventor： Jianhui HUANG , Min QIAO , Pingping HUANG , Yong ZHU , Yajuan LYU , Ying LI
Abstract: Embodiments of the present disclosure disclose a visual question answering model, an electronic device and a storage medium. The visual question answering model includes an image encoder and a text encoder. The text encoder is configured to perform pooling on a word vector sequence of a question text inputted, so as to extract a semantic representation vector of the question text; and the image encoder is configured to extract an image feature of a given image in combination with the semantic representation vector.
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Patent Agency Ranking
公开(公告)号：US20180352043A1
公开(公告)日：2018-12-06
申请号：US15942276
申请日：2018-03-30
Inventor： Hao LIU , Kai LIU , Yajuan LYU
Abstract: The present disclosure discloses an artificial intelligence based method and apparatus for pushing news. A specific embodiment of the method includes: determining at least one news subject from a news text of to-be-pushed news; extracting, from the news text, text fragments respectively associated with news subjects; generating, for each of the news subjects, a subject tag based on the extracted text fragment through a deep learning method; and pushing the to-be-pushed news based on the at least one news subject and the generated subject tag. This embodiment may improve the effectiveness of news pushing.
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公开(公告)号：US20190012377A1
公开(公告)日：2019-01-10
申请号：US16018983
申请日：2018-06-26
Inventor： Jiachen LIU , Bolei HE , Xinyan XIAO , Yajuan LYU , Xiaoxu FEI
Abstract: The present disclosure provides a method and a device for generating a text tag. The method includes: performing keyword extraction using strategies corresponding to respective tag types on a target text, to obtain one or more candidate tags of the respective tag types for the target text, wherein the tag type includes at least one of an entity word, a segment text and a topic; performing reduplication removing between different tag types on the one or more candidate tags of the respective tag types to obtain one or more validated candidate tags; and determining one or more target tags of the target text based on the one or more validated candidate tags.
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4.发明申请公开(公告)号：US20210319335A1
公开(公告)日：2021-10-14
申请号：US17037612
申请日：2020-09-29
Inventor： Wenbin JIANG , Huanyu ZHOU , Meng TIAN , Ying LI , Xinwei FENG , Xunchao SONG , Pengcheng YUAN , Yajuan LYU , Yong ZHU
Abstract: The present disclosure discloses a question analysis method, a device, a knowledge base question answering system and an electronic equipment. The method includes: analyzing a question to obtain N linearized sequences, N being an integer greater than 1; converting the N linearized sequences into N network topology maps; separately calculating a semantic matching degree of each of the N network topology maps to the question; and selecting a network topology map having a highest semantic matching degree to the question as a query graph of the question from the N network topology maps. According to the technology of the present disclosure, the query graph of the question can be obtained more accurately, and the accuracy of the question to the query graph is improved, thereby improving the accuracy of question analysis.
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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：US20200210468A1
公开(公告)日：2020-07-02
申请号：US16705749
申请日：2019-12-06
Inventor： Guocheng NIU , Bolei HE , Chengxiang LIU , Xinyan XIAO , Yajuan LYU
IPC: G06F16/36 , G06N3/08 , G06F40/295 , G06F40/30
Abstract: The present disclosure provides 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.
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