Abstract
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.
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© 2006 Springer-Verlag Berlin Heidelberg
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Phillips, P., Lee, I. (2006). Mining Positive Associations of Urban Criminal Activities Using Hierarchical Crime Hot Spots. In: Chen, H., Wang, FY., Yang, C.C., Zeng, D., Chau, M., Chang, K. (eds) Intelligence and Security Informatics. WISI 2006. Lecture Notes in Computer Science, vol 3917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11734628_15
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DOI: https://doi.org/10.1007/11734628_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33361-6
Online ISBN: 978-3-540-33362-3
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