公开(公告)号：US12210982B2

公开(公告)日：2025-01-28

申请号：US17872318

申请日：2022-07-25

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

Inventor： Wenbin Jiang ,  Yajuan Lyu ,  Yong Zhu ,  Hua Wu ,  Haifeng Wang

IPC: G06F40/30 ,  G06F40/20 ,  G06N5/04

Abstract: The present disclosure provides a method for processing intelligent question-answering, an intelligent question-answering system, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies, such as machine learning technologies, natural language processing technologies, or the like. An implementation includes: acquiring an input question and input data information; and based on the question, the data information and a plurality of knowledge bases, deciding an answer to the question by multilayer appreciation using a plurality of understanding module layers.

公开(公告)号：US20230112385A1

公开(公告)日：2023-04-13

申请号：US18079846

申请日：2022-12-12

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

Inventor： Qi Wang ,  Zhifan Feng ,  Chunguang Chai ,  Yong Zhu

IPC: G06F16/432 ,  G06F16/483

Abstract: A method of obtaining an event information, an electronic device, and a storage medium, which relate to a field of artificial intelligence, in particular to fields of knowledge graph and deep learning technologies. A specific implementation solution of the method of obtaining the event information includes: determining, according to a query information in data to be processed, a first key information describing an event; determining, according to multimedia data in the data to be processed, a second key information describing an event, wherein the multimedia data includes data obtained by querying based on the query information; and fusing the first key information and the second key information, so as to obtain an event information of a target event described by the data to be processed.

公开(公告)号：US11151179B2

公开(公告)日：2021-10-19

申请号：US16362584

申请日：2019-03-22

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

Inventor： Shuangjie Li ,  Yabing Shi ,  Haijin Liang ,  Yang Zhang ,  Yong Zhu

IPC: G06F16/335

Abstract: Provided are a method, an apparatus and an electronic device for determining a knowledge sample data set, the method includes: acquiring a preset number of SPO triplet formats and source texts; acquiring, according to the SPO triplet formats, n SPO entries corresponding to the SPO triplet formats; searching, in the source texts, m first texts that match the n SPO entries, and generating a first knowledge sample data set; determining k second texts that meet the SPO triplet formats from the m first texts and generating a second knowledge sample data set; generating a target knowledge sample data set according to the first knowledge sample data set and the second knowledge sample data set. In the embodiments, the knowledge sample data set is automatically generated, the volume generation speed is fast, the cost is low, and the data size that can be produced is large, thus meeting the training requirement.

公开(公告)号：US12204851B2

公开(公告)日：2025-01-21

申请号：US17864636

申请日：2022-07-14

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

Inventor： Tongyang Liu ,  Shu Wang ,  Wanli Chang ,  Wei Zheng ,  Zhifan Feng ,  Chunguang Chai ,  Yong Zhu

IPC: G06F40/211 ,  G06F40/109 ,  G06F40/30 ,  G06N3/08

Abstract: A method for generating a pre-trained language model, includes: obtaining sample files; obtaining typography structure information and text information of the sample files by parsing the sample files; obtaining a plurality of task models of a pre-trained language model; obtaining a trained pre-trained language model by jointly training the pre-trained language model and the plurality of task models according to the typography structure information and the text information; and generating a target pre-trained language model by fine-tuning the trained pre-trained language model according to the typography structure information and the text information.

公开(公告)号：US11755654B2

公开(公告)日：2023-09-12

申请号：US17173318

申请日：2021-02-11

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Qian Li ,  Yabing Shi ,  Ye Jiang ,  Chunguang Chai ,  Yong Zhu

IPC: G06F16/90 ,  G06F16/9032 ,  G06F16/906 ,  G06F16/903 ,  G06F40/30 ,  G06N3/049

CPC classification number: G06F16/90332 ,  G06F16/906 ,  G06F16/90335 ,  G06F40/30 ,  G06N3/049

Abstract: Provided by the present disclosure is a new category tag mining method, involving the field of knowledge graph technology, and including: obtaining a plurality of queries during a current preset time period; labeling a category tag on each query of the plurality of queries, by using a pre-trained sequence labeling model, to extract the category tag currently corresponding to the query from the query; and removing a category tag already existing in a preset current category tag library from category tags currently corresponding to all the queries, and determining a remaining category tag as a new category tag. The present disclosure also provides an electronic device and a non-transitory computer-readable storage medium.

公开(公告)号：US12019990B2

公开(公告)日：2024-06-25

申请号：US17124030

申请日：2020-12-16

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

Inventor： Haifeng Wang ,  Wenbin Jiang ,  Yajuan Lv ,  Yong Zhu ,  Hua Wu

IPC: G06N20/00 ,  G06F18/214 ,  G06F18/2413 ,  G06F40/279 ,  G06F40/30 ,  G06N5/022

CPC classification number: G06F40/30 ,  G06F18/214 ,  G06F18/24147 ,  G06F40/279 ,  G06N5/022

Abstract: The present application discloses a text processing method and device based on natural language processing and a knowledge graph, and relates to the in-depth field of artificial intelligence technology. A specific implementation is: an electronic device uses a joint learning model to obtain a semantic representation, which is obtained by the joint learning model by combining knowledge graph representation learning and natural language representation learning, it combines a knowledge graph representation learning and a natural language representation learning, compared to using only the knowledge graph representation learning or the natural language representation learning to learn semantic representation of a prediction object, factors considered by the joint learning model are more in quantity and comprehensiveness, so accuracy of semantic representation can be improved, and thus accuracy of text processing can be improved.

公开(公告)号：US12222977B2

公开(公告)日：2025-02-11

申请号：US18080432

申请日：2022-12-13

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

Inventor： Shuai Chen ,  Qi Wang ,  Zhifan Feng ,  Chunguang Chai ,  Yong Zhu

IPC: G06F18/25 ,  G06F16/43 ,  G06F16/483 ,  G06F18/22 ,  G06N5/02

Abstract: A method of processing multimedia data, a device, and a medium, which relates to a field of an artificial intelligence technology, in particular to fields of knowledge graph and deep learning. The method of processing the multimedia data includes: recognizing the multimedia data so as to obtain at least one key information of the multimedia data; querying a predetermined knowledge base according to the at least one key information, so as to determine a multimedia name associated with the at least one key information and an association degree between the multimedia name and the at least one key information; and determining, in the multimedia name, a name of the multimedia data based on a similarity between alternative multimedia data for the multimedia name and the multimedia data, in response to the association degree being less than a first threshold value.

公开(公告)号：US12094208B2

公开(公告)日：2024-09-17

申请号：US17502173

申请日：2021-10-15

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

Inventor： Hu Yang ,  Feng He ,  Qi Wang ,  Zhifan Feng ,  Chunguang Chai ,  Yong Zhu

IPC: G06K9/62 ,  G06F18/214 ,  G06F18/241 ,  G06F18/25 ,  G06N20/00 ,  G06V10/22 ,  G06V10/40 ,  G06V10/70 ,  G06V10/764 ,  G06V10/80 ,  G06V10/82 ,  G06V20/40 ,  G06V20/62 ,  G06V20/70 ,  G10L15/08 ,  G06N3/08 ,  G06V30/10

CPC classification number: G06V20/46 ,  G06F18/214 ,  G06F18/241 ,  G06F18/253 ,  G06N20/00 ,  G06V10/22 ,  G06V10/40 ,  G06V10/764 ,  G06V10/768 ,  G06V10/806 ,  G06V10/82 ,  G06V20/41 ,  G06V20/635 ,  G06V20/70 ,  G10L15/08 ,  G06N3/08 ,  G06V30/10

Abstract: The present disclosure discloses a video classification method, an electronic device and a storage medium, and relates to the field of computer technologies, and particularly to the field of artificial intelligence technologies, such as knowledge graph technologies, computer vision technologies, deep learning technologies, or the like. The video classification method includes: extracting a keyword in a video according to multi-modal information of the video; acquiring background knowledge corresponding to the keyword, and determining a text to be recognized according to the keyword and the background knowledge; and classifying the text to be recognized to obtain a class of the video.