We tackle a fundamental problem in our paper: crime rate inference at the neighborhood level. Tradi- tional approaches have used demographics and geographical ...

We tackle a fundamental problem in our paper: crime rate inference at the neighborhood level. Traditional approaches have used demographics and geographical ...

We tackle a fundamental problem in our paper: crime rate inference at the neighborhood level. Traditional approaches have used demographics and geographical ...

We tackle a fundamental problem in our paper: crime rate inference at the neighborhood level. Traditional approaches have used demographics and geographical ...

In summary, the contribution of this paper are: 1) We study an old but very important crime inference problem by utilizing new urban data: POIs and taxi flows.

Large-scale Point-Of-Interest data and taxi flow data in the city of Chicago, IL in the USA is used and significantly improved performance in crime rate ...

Crime Rate Inference with Big Data. Hongjian Wang† , Daniel Kifer‡ , Corina Graif$ , Zhenhui Li†. † College of Information Sciences and Technology

We tackle a fundamental problem in our paper: crime rate inference at the neighborhood level. Traditional approaches have used demographics and geographical ...

We tackle a fundamental problem in our paper: crime rate inference at the neighborhood level. Traditional approaches have used demographics and geographical ...

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