Mining positive associations of urban criminal activities using hierarchical crime hot spots

We present a framework for discovering positive associations in urban crime datasets using hierarchical clustering and an association test based on a hybrid minimum bounding circle and average bounding circle approach. We justify the virtue of our framework by comparing its computational speed and quality of associations using real crime datasets.

Lecture Notes in Computer Science

WISI 2006 Intelligence and Security Informatics International Workshop

3917

1611-3349

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