公开(公告)号：US20210018332A1

公开(公告)日：2021-01-21

申请号：US16931529

申请日：2020-07-17

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

Inventor： Chongli ZHU ,  Hongwei XIE ,  Kuan SONG

IPC: G01C21/00 ,  G06N3/08 ,  G01C21/36 ,  G06K9/62

Abstract: Embodiments of the present disclosure provide a POI name matching method, apparatus, device and storage medium, which obtain a first POI name and a second POI name that are to be matched; obtain a similarity between the first POI name and the second POI name according to a pre-trained network model; and determine that a first POI and a second POI are the same POI entity in name semantics when the similarity is higher than a preset threshold. The embodiments determine a semantic similarity between POI names through the pre-trained network model, which realizes the POI name matching without needing to maintain a large number of manual rules and depending on similarity feature of manually extracted POI names, and has higher accuracy, better maintainability and higher processing efficiency.

公开(公告)号：US20240273297A1

公开(公告)日：2024-08-15

申请号：US18642593

申请日：2024-04-22

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

Inventor： Yu LI ,  Jiawei ZHENG ,  Xinjiang LU ,  Hongwei XIE ,  Xuejiao LIN ,  Jingbo ZHOU

IPC: G06F40/295

CPC classification number: G06F40/295

Abstract: An entity recognition method, a model training method, an electronic device, and a medium, which relate to fields of artificial intelligence, information acquiring technologies. The entity recognition method includes: extracting specified entities from a text in a source file of a webpage to be recognized, and acquiring a text encoding result for each specified entity; determining a text block formed by each specified entity in the webpage, and encoding a relative layout information between each two text blocks, to obtain a position encoding result; constructing a triple by the position encoding result for each two text blocks and the text encoding results for respective specified entities of the two text blocks; and performing a graph convolution on each triple to obtain a relation recognition result for the webpage to be recognized, where the relation recognition result indicates whether an association exists between each two text blocks in the webpage.