• Korean Security Journal
• /
• no.34
• /
• pp.313-336
• /
• 2013

The purpose of this study is to derive an optimal regression model for occurrences of major crimes on a security company's stock price through identifying precedence of the occurrences of major crimes on the security company's stock price, relationship between the occurrences of major crimes and the security company's stock price. Followings are the results of this study. First, the occurrences of murder crime, robbery crime, rape crime, theft crime move along the security company's monthly stock price simultaneously, and the occurrence of violence crime precedes 6 months to the security company's monthly stock price depending on the results of cross-correlation analysis of precedence of occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime on the security company's monthly stock price. Second, the explanation of the occurrences of robbery crime, rape crime, theft crime on the security company's monthly stock price is 61.7%($R^2$ = .617) excluding murder crime, violence crime depending on the results of multiple regression analysis(stepwise method) by putting the occurrences of major crimes, such as murder crime, robbery crime, rape crime, theft crime, violence crime into the security company's monthly stock price.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.3
• /
• pp.95-103
• /
• 2012

Modern society is experiencing a variety of crimes, and to prevent crime is being studied. Existing studies related to the crime of crimes that occur on spatial analysis and geographic information, or to analyze the type of criminal offense of studies have been conducted, However the existing studies of the geographical and psychological crime that occurs throughout the study area and by analyzing the motives for the crime prevention research is the most. In this paper, we introduce Markov processor model for predicting the crime is present. Of several crimes, murder, government official crimes, the incidence of violent crime has occurred over time by using the predicted incidence of crime. Presented in this paper, predictive modeling is used in a crime occurred in the average duration of the overall average number of crimes that occurred in the one-year average, which recently labeled as the average prediction was compared to if you can increase the likelihood, recent average to apply to increase the probability of the prediction that crime have been investigated.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.4
• /
• pp.163-172
• /
• 2012

Modern society, various great strength crimes are producing. After all crimes happen, it is most important that prevent crime beforehand than that cope. So, many research studied to prevent various crime. However, existing method of studies are to analyze and prevent by society and psychological factors. Therefore we wishes to achieve research to forecast crime by time using Markov chain method. We embody modelling for crime occurrence estimate by crime type time using crime occurrence number of item data that is collected about 5 great strength offender strength, murder, rape, moderation, violence. And examined propriety of crime occurrence estimate modelling by time that propose in treatise that compare crime occurrence type crime occurrence estimate price and actuality occurrence value. Our proposed crime occurrence estimate techniques studied to apply maximum value by critcal value about great strength crime such as strength, murder, rape etc. actually, and heighten crime occurrence estimate probability by using way to apply mean value about remainder crime in this paper. So, we wish to more study about wide crime case and as the crime occurrence estimate rate and actuality value by time are different in crime type hereafter applied examples investigating.

• Journal of the Korea Convergence Society
• /
• v.9 no.5
• /
• pp.15-20
• /
• 2018

In modern society, crime is one of the major social problems. Crime has a great impact not only on victims but also on those around them. It is important to predict crimes before they occur and to prevent crime. Various studies have been conducted to predict crime. One of the most important factors in predicting crime is frequency of crime occurrence. The frequency of crime is widely used as basic data for predicting crime. However, the frequency of crime occurrence is announced about 2 years after the statistical processing period. In this paper, we propose a frequency analysis of crime - related key words retrieved from the web as a way to indirectly grasp the frequency of crime occurrence. The relationship between the number of frequency of crime occurrence and frequency of actual crime occurrence was analyzed by correlation coefficient.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.9
• /
• pp.229-236
• /
• 2016

In the past, crime prediction methods utilized previous records to accurately predict crime occurrences. Yet these crime prediction models had difficulty in updating immense data. To enhance the crime prediction methods, some approaches used social network service (SNS) data in crime prediction studies, but the relationship between SNS data and crime records has not been studied thoroughly. Hence, in this paper, we analyze the relationship between SNS data and criminal occurrences in the perspective of crime prediction. Using Latent Dirichlet Allocation (LDA), we extract tweets that included any words regarding criminal occurrences and analyze the changes in tweet frequency according to the crime records. We then calculate the number of tweets including crime related words and investigate accordingly depending on crime occurrences. Our experimental results demonstrate that there is a difference in crime related tweet occurrences when criminal activity occurs. Moreover, our results show that SNS data analysis will be helpful in crime prediction model as there are certain patterns in tweet occurrences before and after the crime.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.5
• /
• pp.235-241
• /
• 2007

AThis research is rather on the crime occurrence of target area's space scope than on the approach to the cause of specific area's crime occurrence from the perspective of the environmental criminology emphasizing the crime prevention. By observing the composition of crime distribution, it is intended to search the strategies of crime prevention actually corresponded to the crime problems. For this, after segmenting the city into six sectors, targeting city crimes in Gwangju metropolitan city, in 2004, the basic materials about the crime frequency are analyzed through dividing the types on the base of the present state of crime occurrence, the types of crime, the locations of crime occurrence, the purposes of buildings, the types of intruders, the forms of intrusions. As a result of research. it is suggested that the activation method of community police activities is necessary for the prevention of community crime prevention.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.221-229
• /
• 2015

The urban crimes that threat individual's safety are parts of the serious social problems. However. the information of crime in Korea has only been provided by forms of hot spots around place of crime, or forms of crime statistics without positional information. Those could not provide enough information to users in identifying the vulnerable areas for substantive crimes. Therefore, this study suggested a methodology of extraction in criminal vulnerable areas by using the spatial information, the statistical information and the public sector information. The crime vulnerable areas were extracted through the grid-based spatial analysis and the overlapping analysis from each of the information. In fact, the extracted areas were able to provide detailed vulnerability information than the traditional hot spot-based crime information. Following the study, the extracted results in crime vulnerable areas have displayed highly coincide with Korea safety map, provided by national disaster management institute, which regards to be able to provide crime risk rating in terms of administrative business in future.

• Korean Security Journal
• /
• no.16
• /
• pp.65-79
• /
• 2008

This study started with the need to have a basic understanding of the crimes related to security guard in Korea. For this purpose, it attempted to analyze the crimes related to security guard occurring in Korea for the years, the cause for those crimes to occur, and the basic cause for those crimes such as criminals' educational level, age, occupation and so forth investigate how those crimes occurred. And ultimately it was intended to provide referential materials for perfect security guard from the stage of its planning to the stage of implementation and termination by analyzing how the machinery of law treated those criminals. This study aimed to help security guards to perform their role by investigating the cause and disposition of crimes related to security guard occurring for the years in order to cope with the emergency situation frequently occurring in the job of security guard. To attain the goal of study, this study attempted to do the following tasks: First, to analyze existing crimes and investigate the crimes related to security guard in order to investigate how the criminal act occurred in relation to the crime related to security guard, numerous kinds of crimes. Second, to investigate in what case the criminal act occurred by analyzing the criminal environment, the yearly, monthly and weekly frequency of those crimes and the like in relation to this criminal act. Third, to grope the alternative to cope effectively with all sorts of dangerous situations on the spot of security guard by analyzing the crimes related to security guard and investigating the effective scheme for coping with it.

• Journal of the Korean Geographical Society
• /
• v.36 no.3
• /
• pp.329-341
• /
• 2001

The purpose of this study focused on the distribution of crimes in Cheongju City. This study emphasized the characteristics of place and spatial pattern of crime in Central Business District(CBD). The crime core areas were delineated and explained through land-use based on fieldwork and GIS analysis For this aim. the police crime data of Cheongju Dongbu(east). Seobu(west) for 1998 were collected In which 3.909 indictable or similar offenses were reported. In this study, Included climes are murder. rape, robbery. arson, theft, burglary, assault and vandalism. Because theme crimes are related with site-specific crime. As a result. land-use patterns are often related to specific type of offenses. The climes in Cheongju City were concentrated in the CBD Most crimes were assaults and thefts Crime areas can be classified by the age of the offender Around Chungang and Pungmul Market in the CBD. the offender＇s ages were 30-50 dominantly Assaults and thefts were concentrated in Songan-gil(street). which is a place teen-ages and youngsters meet frequently The result of the buffering analysis with roads, explained 40% of crime within a 30m buffer area( including both sides) of a principal road The rest of the climes mainly occurred in the vicinity of narrow streets and alleys.

• Journal of Satellite, Information and Communications
• /
• v.10 no.2
• /
• pp.40-45
• /
• 2015

In this paper, we proposed and implemented a crime prediction algorithm based upon crime influential factors. To collect the crime-related big data, we used a data which had been collected and was published in the supreme prosecutors' office. The algorithm analyzed various crime patterns in Seoul from 2011 to 2013 using the spatial statistics analysis. Also, for the crime prediction algorithm, we adopted a Bayesian network. The Bayesian network consist of various spatial, populational and social characteristics. In addition, for the more precise prediction, we also considered date, time, and weather factors. As the result of the proposed algorithm, we could figure out the different crime patterns in Seoul, and confirmed the prediction accuracy of the proposed algorithm.