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Multi-density crime predictor: an approach to forecast criminal activities in multi-density crime hotspots

Abstract The increasing pervasiveness of ICT technologies and sensor infrastructures is enabling police departments to gather and store increasing volumes of spatio-temporal crime data. This offers the opportunity to apply data analytics methodologies to extract useful crime predictive models, which...

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Principais autores: Eugenio Cesario, Paolo Lindia, Andrea Vinci
Format: Artigo
Sprog:Inglês
Udgivet: SpringerOpen 2024-05-01
Serier:Journal of Big Data
Fag:
Crime data mining
Crime forecasting
Crime hotspots
LSTM
Multi-density clustering
Urban crime data analysis
Online adgang:https://doi.org/10.1186/s40537-024-00935-4
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