<div>Dashboard has been around for a long time, and many have been developed as a governing and monitoring tool in city management, such as crime monitoring. However, the majority of crime dashboards function as a visualization tool and few of them has been specifically developed for crime analysis and prediction.</div><div>This thesis focuses on the development of geospatially-enabled crime dashboards with
spatial analysis capabilities for supporting crime analysis and prediction. A prototype has been
designed and implemented to support the understanding of crime events for crime reduction efforts.
This dashboard will assist policy makers and leaders in crime fighting by visualizing basic
statistical information of crimes, revealing their spatial and temporal patterns, identifying crime
clusters, and analyzing relationships between crimes and other factors. Based on the criteria
developed in this thesis, the prototype confirmed its ability of enhancing the understanding of
crime events.<br></div>
Design and Implementation of the Compound Noun Segmentation Algorithm Based on Statistical Information
