Urban crime is an ongoing problem in metropolitan development and attracts general concern from the international community. As an effective means of defending urban safety, crime prediction plays a crucial role in patrol force allocation and public safety. However, urban crime data is a macro result of crime patterns overlapped by various irrelevant factors that cause inhomogeneous noises—local outliers and irregular waves. These noises might obstruct the learning process of crime prediction models and result in a deviation of performance. To tackle the problem, we propose a novel paradigm of &lt;underline&gt;Du&lt;/underline&gt;al-&lt;underline&gt;ro&lt;/underline&gt;bust Enhanced Spatial-temporal Learning &lt;underline&gt;Net&lt;/underline&gt;work (DuroNet), an encoder-decoder architecture that possesses an adaptive robustness for reducing the effect of outliers and waves. The robustness is mainly reflected on two aspects. One is a locality enhanced module that employs local temporal context information to smooth the deviation of outliers and dynamic spatial information to assist in understanding normal points. The other is a self-attention-based pattern representation module to weaken the effect of irregular waves by learning attentive weights. Finally, extensive experiments are conducted on two real-world crime datasets before and after adding Gaussian noises. The results demonstrate the superior performance of our DuroNet over the state-of-the-art methods.

Kaixi Hu

Lin Li

Jianquan Liu

Daniel Sun

ACM Transactions on Internet Technology

ACM TRANSACTIONS ON INTERNET TECHNOLOGY (TOIT) 汇集了许多计算学科，包括计算机软件工程、计算机编程语言、中间件、数据库管理、安全性、知识发现和数据挖掘、网络和分布式系统、通信、性能和可扩展性等。TOIT 将涵盖各个学科的结果和作用以及它们之间的关系。

ACM Transactions on Internet Technology (TOIT) brings together research from various computer science disciplines, including software engineering, programming languages, middleware, database management, security, knowledge discovery and data mining, networking and distributed systems, communication, performance, and scalability. TOIT focuses on the results and interrelations of these disciplines.

《ACM Transactions on Internet Technology (TOIT)》汇集了多个计算机学科的研究成果，包括计算机软件工程、编程语言、中间件、数据库管理、安全性、知识发现与数据挖掘、网络与分布式系统、通信、性能与可扩展性等。TOIT 关注这些学科的研究成果及其相互关系。

DuroNet

A novel paradigm of Dual-robust Enhanced Spatial-temporal Learning Network (DuroNet) is proposed, an encoder-decoder architecture that possesses an adaptive robustness for reducing the effect of outliers and waves.

Category	Quartile
计算机科学	3
计算机科学, 计算机信息系统	3
计算机科学, 计算机软件工程	3

DuroNet

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Journal Info

Category	Quartile
COMPUTER SCIENCE, SOFTWARE ENGINEERING	1