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Guifeng Li

dblp:242/1083 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 50% Bioinformatics and computational biology · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities › public administration
public services
0.812024
IBCA: An Intelligent Platform for Social Insurance Benefit Qualification Status Assessment · AAAI 2024
Bioinformatics and computational biology › survival analysis
survival prediction
0.812024
IBCA: An Intelligent Platform for Social Insurance Benefit Qualification Status Assessment · AAAI 2024

Methods — techniques the papers use, named apart from their topics

variational autoencoder · 0.8monte carlo dropout · 0.8missing value interpolation · 0.8gated recurrent unit · 0.8
YearPublicationVenuePosition
2024 IBCA: An Intelligent Platform for Social Insurance Benefit Qualification Status Assessment
abstract
Social insurance benefits qualification assessment is an important task to ensure that retirees enjoy their benefits according to the regulations. It also plays a key role in curbing social security frauds. In this paper, we report the deployment of the Intelligent Benefit Certification and Analysis (IBCA) platform, an AI-empowered platform for verifying the status of retirees to ensure proper dispursement of funds in Shandong province, China. Based on an improved Gated Recurrent Unit (GRU) neural network, IBCA aggregates missing value interpolation, temporal information, and global and local feature extraction to perform accurate retiree survival rate prediction. Based on the predicted results, a reliability assessment mechanism based on Variational Auto-Encoder (VAE) and Monte-Carlo Dropout (MC Dropout) is executed to perform reliability assessment. Deployed since November 2019, the IBCA platform has been adopted by 12 cities across the Shandong province, handling over 50 terabytes of data. It has empowered human resources and social services, civil affairs, and health care institutions to collaboratively provide high-quality public services. Under the IBCA platform, the efficiency of resources utilization as well as the accuracy of benefit qualification assessment have been significantly improved. It has helped Dareway Software Co. Ltd earn over RMB 50 million of revenue.
Yuliang Shi, Lin Cheng 0007, Guifeng Li, Xiaoli Tang 0001, Han Yu 0001, Zhiqi Shen 0001, Cyril Leung
AAAI5