Crime Analysis and Prediction Using Data Mining

被引:0
作者
Sathyadevan, Shiju [1 ]
Devan, M. S. [1 ]
Gangadharan, Surya S. [2 ]
机构
[1] Amrita Vishwa Vidyapeetham, Amrita Ctr Cyber Secur, Amritapuri, Kerala, India
[2] Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India
来源
2014 FIRST INTERNATIONAL CONFERENCE ON NETWORKS & SOFT COMPUTING (ICNSC) | 2014年
关键词
Naive Bayes; Apriori algorithm; Decision tree; NER; Mongo DB; Neo4j; GraphDB;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Crime analysis and prevention is a systematic approach for identifying and analyzing patterns and trends in crime. Our system can predict regions which have high probability for crime occurrence and can visualize crime prone areas. With the increasing advent of computerized systems, crime data analysts can help the Law enforcement officers to speed up the process of solving crimes. Using the concept of data mining we can extract previously unknown, useful information from an unstructured data. Here we have an approach between computer science and criminal justice to develop a data mining procedure that can help solve crimes faster. Instead of focusing on causes of crime occurrence like criminal background of offender, political enmity etc we are focusing mainly on crime factors of each day.
引用
收藏
页码:406 / 412
页数:7
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