公开(公告)号：US20190228320A1

公开(公告)日：2019-07-25

申请号：US16255369

申请日：2019-01-23

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

Inventor： Zhifan FENG ,  Chao LU ,  Ye XU ,  Zhou FANG ,  Yong ZHU ,  Ying LI

IPC: G06N5/02 ,  G06N20/00 ,  G06K9/62

Abstract: Systems, methods, terminals, and computer readable storage medium for normalizing entities in a knowledge base. A method for normalizing entities in a knowledge base includes acquiring a set of entities in the knowledge base, pre-segmenting the set of entities in a plurality of segmenting modes, performing a sample construction based on the result of pre-segmentation to extract a key sample, performing a feature construction based on the result of pre-segmentation to extract a similar feature, performing a normalizing determination on each pair of entities with at least one normalization model using the key sample and the similar feature to determine whether entities in each pair are the same, and grouping results of the normalizing determination.

公开(公告)号：US20210217504A1

公开(公告)日：2021-07-15

申请号：US17023998

申请日：2020-09-17

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

Inventor： Zhou FANG ,  Shuangjie LI ,  Yabing SHI ,  Ye JIANG

IPC: G16H20/10 ,  G06F40/58 ,  G06N20/00 ,  G16H40/67 ,  G16H40/63

Abstract: The present disclosure relates to the field of medical data processing based on natural language processing. Embodiments of the present disclosure disclose a method and apparatus for verifying a medical fact. The method may include: acquiring a description text of the medical fact; selecting a relevant paragraph related to the description text of the medical fact from a medical document; and inputting the description text of the medical fact and the corresponding relevant paragraph into a trained discrimination model for authenticity judgment, to obtain a verification result of the medical fact, the discrimination model being pre-trained based on a medical text paragraph pair extracted from the medical document, and being iteratively adjusted using a medical fact sample set including authenticity labeling information after the pre-training.

公开(公告)号：US20220027766A1

公开(公告)日：2022-01-27

申请号：US17493365

申请日：2021-10-04

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

Inventor： Zhou FANG ,  Yabing SHI ,  Ye JIANG ,  Chunguang CHAI

IPC: G06N5/04 ,  G06N20/00

Abstract: A method for an industry text increment, as well as an electronic device and a computer readable storage medium for the same are provided. The method may include: acquiring an original industry text in a target industry field, an order of magnitude of a number of the original industry text being smaller than a preset first order of magnitude; and performing a sample incremental processing on the original industry text by using a distant supervision method, to obtain increased industry texts, an order of magnitude of a number of the increased industry texts is greater than a preset second order of magnitude, wherein the preset second order of magnitude is not smaller than the preset first order of magnitude.

公开(公告)号：US20190220752A1

公开(公告)日：2019-07-18

申请号：US16213610

申请日：2018-12-07

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

Inventor： Ye XU ,  Zhifan FENG ,  Chao LU ,  Yang ZHANG ,  Zhou FANG ,  Shu WANG ,  Yong ZHU ,  Ying LI

IPC: G06N5/02 ,  G06N5/04 ,  G06N7/00 ,  G06F16/28 ,  G06F16/901 ,  G06F16/951 ,  G06F16/955 ,  G06F16/2458 ,  G06K9/62

CPC classification number: G06N5/022 ,  G06F16/2468 ,  G06F16/288 ,  G06F16/9024 ,  G06F16/951 ,  G06F16/955 ,  G06K9/6215 ,  G06K9/6276 ,  G06N5/04 ,  G06N7/005

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.