TY - JOUR AU - Mohd Ansari AU - Anand Prakash AU - Dr Mainuddin PY - 2018/06/26 Y2 - 2024/03/29 TI - Application of Spatiotemporal Fuzzy C-Means Clustering for Crime Spot Detection JF - Defence Science Journal JA - DSJ VL - 68 IS - 4 SE - Computers & Systems Studies DO - 10.14429/dsj.68.12518 UR - https://publications.drdo.gov.in/ojs/index.php/dsj/article/view/12518 AB - The various sources generate large volume of spatiotemporal data of different types including crime events. In order to detect crime spot and predict future events, their analysis is important. Crime events are spatiotemporal in nature; therefore a distance function is defined for spatiotemporal events and is used in Fuzzy C-Means algorithm for crime analysis. This distance function takes care of both spatial and temporal components of spatiotemporal data. We adopt sum of squared error (SSE) approach and Dunn index to measure the quality of clusters. We also perform the experimentation on real world crime data to identify spatiotemporal crime clusters.  ER -