Association Rule Mining on Crime Pattern Mining

被引：0
|
作者：
Roy, Suman [1 ]
Bordoloi, Ripunjoy [1 ]
Das, Kayboy Jyoti [1 ]
Kumar, Santosh [1 ]
Muchahari, Monoj Kumar [1 ]
机构：
[1] Assam Kaziranga Univ, Dept IT, Jorhat, Assam, India
来源：
2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2021) | 2021年
关键词：
Association rules; similar crime patterns; FP-Growth algorithm;
D O I：
10.1109/ComPE53109.2021.9752393
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Recognizing similar offenses during a offender inquiry is a major position of offense analysts. Through the help of pattern finding technique, crime specialists discover new pattern types from dataset. Over the past few years, association rule mining is implemented to analyze crime data from real datasets to find exact trends in crime. The indicated paper has worked with the (FP Growth algorithm) to determine similar crime patterns. Observational results are presented that will help crime experts predict crime and determine the maximum chances of corruption in a particular area.
引用
收藏
页码：269 / 272
页数：4
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