TY - GEN
T1 - Geospatial-temporal analysis andclassification of criminal data in Manila
AU - Baculo, Maria Jeseca C.
AU - Marzan, Charlie S.
AU - De Dios Bulos, Remedios
AU - Ruiz, Conrado
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/4
Y1 - 2017/12/4
N2 - The use of technology on criminal data has proven to be a valuable tool in forecasting criminal activity. Crime prediction is one of the approaches that help reduce and deter crimes. In this paper, we perform geospatial analysis using the kernel density estimation in ArcGIS 10 to identify the spatiotemporal hotspots in Manila, the most densely populated city in the Philippines. We also compared the performance measures of the BayesNet, Naïve Bayes, J48, Decision Stump, and Random Forest classifiers in predicting possible crime activities. The results presented in this paper aim to provide insights on crime patterns as well as help law enforcement agencies design and implement approaches to respond to criminal activities.
AB - The use of technology on criminal data has proven to be a valuable tool in forecasting criminal activity. Crime prediction is one of the approaches that help reduce and deter crimes. In this paper, we perform geospatial analysis using the kernel density estimation in ArcGIS 10 to identify the spatiotemporal hotspots in Manila, the most densely populated city in the Philippines. We also compared the performance measures of the BayesNet, Naïve Bayes, J48, Decision Stump, and Random Forest classifiers in predicting possible crime activities. The results presented in this paper aim to provide insights on crime patterns as well as help law enforcement agencies design and implement approaches to respond to criminal activities.
KW - Classifiers
KW - Crime analysis
KW - Predictive methods
UR - http://www.scopus.com/inward/record.url?scp=85043457649&partnerID=8YFLogxK
U2 - 10.1109/CIAPP.2017.8167050
DO - 10.1109/CIAPP.2017.8167050
M3 - Conference contribution
AN - SCOPUS:85043457649
T3 - 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017
SP - 6
EP - 11
BT - 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017
Y2 - 8 September 2017 through 11 September 2017
ER -