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Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction

Zi-Yang Wu Fan Liu Jin-Dong Han Yu-Xuan Liang Hao Liu

Journal of Computer Science & Technology2026，Vol.41Issue(2)：P.669-683,15.

Journal of Computer Science & Technology2026，Vol.41Issue(2)：P.669-683,15.DOI:10.1007/s11390-025-5404-1

Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction

Zi-Yang Wu ¹Fan Liu ¹Jin-Dong Han ²Yu-Xuan Liang ³Hao Liu⁴

作者信息

1. Thrust of Artificial Intelligence,The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511458,China
2. Division of Emerging Interdisciplinary Areas,The Hong Kong University of Science and Technology,Hong Kong,China
3. Thrust of Intelligent Transportation&the Thrust of Data Science and Analytics,The Hong Kong University of Science and Technology(Guangzhou),Guangzhou 511458,China
4. Thrust of Artificial Intelligence,The Hong Kong University of Science and Technology(Guangzhou)Guangzhou 511458,China Department of Computer Science and Engineering,The Hong Kong University of Science and Technology Hong Kong,China
折叠

摘要

关键词

multi-type crime prediction/spatio-temporal prediction/mixture-of-experts

分类

社会科学

引用本文复制引用

Zi-Yang Wu,Fan Liu,Jin-Dong Han,Yu-Xuan Liang,Hao Liu..Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction[J].Journal of Computer Science & Technology,2026,41(2):P.669-683,15.

基金项目

supported by the National Key Research and Development Program of China under Grant No.2023YFF0725004 （）

the National Natural Science Foundation of China under Grant No.92370204 （）

the Guangzhou Basic and Applied Basic Research Program under Grant No.2024A04J3279 （）

the Education Bureau of Guangzhou Municipality. （）

Journal of Computer Science & Technology

ISSN：1000-9000

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