公开(公告)号：US20180373787A1

公开(公告)日：2018-12-27

申请号：US15859800

申请日：2018-01-02

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Chengxiang LIU ,  Xinyan XIAO

IPC: G06F17/30 ,  G06F17/27

Abstract: A method for recommending a text content based on a concern, a computer device, and a non-transitory computer readable storage medium are provided. The method includes: acquiring a query input by a user, and acquiring a reference text content selected by the user from search results corresponding to the query; generating a term vector of the query according to a term relative to the query in the reference text content; determining the concern of the user from a plurality of reference concerns according to similarities between the term vector of the query and term vectors of the plurality of reference concerns; and recommending the text content matched with the concern to the user.

公开(公告)号：US20210383121A1

公开(公告)日：2021-12-09

申请号：US17115263

申请日：2020-12-08

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Chengxiang LIU ,  Hao LIU ,  Bolei HE

IPC: G06K9/00 ,  G06K9/72 ,  G06K9/62

Abstract: A method for generating a tag of a video, an electronic device, and a storage medium are related to a field of natural language processing and deep learning technologies. The detailed implementing solution includes: obtaining multiple candidate tags and video information of the video; determining first correlation information between the video information and each of the multiple candidate tags; sorting the multiple candidate tags based on the first correlation information to obtain a sort result; and generating the tag of the video based on the sort result.

公开(公告)号：US20200210468A1

公开(公告)日：2020-07-02

申请号：US16705749

申请日：2019-12-06

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

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.