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http://dx.doi.org/10.9708/jksci.2015.20.1.093

A study to Predictive modeling of crime using Web traffic information  

Park, Jung-Min (Dept. of Computer Science & Engineering, Kongju national University)
Chung, Young-Suk (Dept. of Computer Science & Engineering, Kongju national University)
Park, Koo-Rack (Dept. of Computer Science & Engineering, Kongju national University)
Publication Information
Journal of the Korea Society of Computer and Information / v.20, no.1, 2015 , pp. 93-101 More about this Journal
Abstract
In modern society, various crimes is occurred. It is necessary to predict the criminal in order to prevent crimes, various studies on the prediction of crime is in progress. Crime-related data, is announced to the statistical processing of once a year from the Public Prosecutor's Office. However, relative to the current point in time, data that has been statistical processing is a data of about two years ago. It does not fit to the data of the crime currently being generated. In This paper, crime prediction data was apply with Naver trend data. By using the Web traffic Naver trend, it is possible to obtain the data of interest level for crime currently being generated. It was constructed a modeling that can predict the crime by using traffic data of the Naver web search. There have been applied to Markov chains prediction theory. Among various crimes, murder, arson, rape, predictive modeling was applied to target. And the result of predictive modeling value was analyzed. As a result, it got the same results within 20%, based on the value of crime that actually occurred. In the future, it plan to advance research for the predictive modeling of crime that takes into the characteristics of the season.
Keywords
Crime prediction; search traffic; Markov chains; trend prediction;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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