公开(公告)号：US20210034993A1

公开(公告)日：2021-02-04

申请号：US16936190

申请日：2020-07-22

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

Inventor： Miao FAN ,  Jizhou HUANG ,  An ZHUO ,  Ying LI ,  Ping LI ,  Haifeng WANG

IPC: G06N5/04 ,  G06N20/00

Abstract: A POI valuation method, apparatus, device and computer storage medium are disclosed. The method comprises: obtaining information of first POIs with known values and information of second POIs with unknown values within a regional range; creating a valuation model which is configured to revaluate a first POI using values of surrounding POIs of the first POI, the surrounding POIs including other first POIs and second POIs within a predetermined range of distance from the first POI, and adjusting values of second POIs in the surrounding POIs using an error between a revaluated value of first POI and the known value of the first POI; training the valuation model until the error is minimized; obtaining the values of the second POIs from the valuation model. The solutions may reduce the requirement for manpower and improve the valuation efficiency as compared with manually valuation of POIs one by one.

公开(公告)号：US20220398465A1

公开(公告)日：2022-12-15

申请号：US17620820

申请日：2021-06-02

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

Inventor： Jizhou HUANG ,  Jingbo ZHOU ,  An ZHUO ,  Ji LIU ,  Haoyi XIONG ,  Dejing DOU ,  Haifeng WANG

IPC: G06N5/02

Abstract: A technical solution relates to a big data technology in the field of artificial intelligence technologies. The technical solution includes: acquiring training data including annotation results of a risk grade of each sample region and a risk grade of a district to which each sample region belongs; and training an initial model including an encoder, a discriminator and a classifier using the training data, and obtaining the risk prediction model using the encoder and the classifier after the training process. The encoder performs a coding operation using region features of the sample regions to obtains a feature representation of each sample region; the discriminator identifies the risk grade of the district to which the sample region belongs according to the feature representation of the sample region; the classifier identifies the risk grade of the sample region according to the feature representation of the sample region.