Crime Rate Prediction with Region Risk and Movement Patterns

Publication Year: 2019 Publication Type : JournalArticle


Location Based Social Network, Foursquare helps us to understand the human movement of a city. It provides data that characterises the volume of movements across regions and Places of Interests (POIs) to explore the crime dynamics of the city. To fully exploit human movement into crime analysis, we propose region risk factor which combines monthly aggregated crime and human movement of a region across different time intervals. Number of features are derived from this risk factor. Extensive experiments with real world data in multiple cities verify the effectiveness of the features.


@article{DBLP:journals/corr/abs-1908-02570, archiveprefix = {arXiv},
    author = {Shakila Khan Rumi and Phillip Luong and Flora D. Salim},
    bibsource = {dblp computer science bibliography,},
    biburl = {},
    eprint = {1908.02570},
    journal = {CoRR},
    timestamp = {Fri, 09 Aug 2019 01:00:00 +0200},
    title = {Crime Rate Prediction with Region Risk and Movement Patterns},
    url = {},
    volume = {abs/1908.02570},
    year = {2019}


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