Highly clustered event sequences are observed in certain types of crime data, such as burglary and gang violence, due to crime-specific patterns of criminal behavior. Similar clustering patterns are observed by seismologists, as earthquakes are well known to increase the risk of subsequent earthquakes, or aftershocks, near the location of an initial event. Space–time clustering is modeled in se...

A. Malathi and Dr. S. Santhosh Baboo Abstract— Crime is a behavior deviation from normal activity of the norms giving people losses and harms. Crimes are a social nuisance and cost our society dearly in several ways. In this paper we look at use of missing value and clustering algorithm for crime data using data mining. We will look at MV algorithm and Apriori algorithm with some enhancements t...

A major challenge facing all law-enforcement and intelligence gathering organizations is accurately and efficiently analyzing the growing volumes of crime data. There has been an enormous increase in the crime in the recent past. The concern about national security has increased significantly since the 26/11 attacks. Crimes are a social nuisance and cost our society dearly in several ways. Here...

We developed Cyber Forensics Ontology for the criminal investigation in cyber space. Cyber crime is classified into cyber terror and general cyber crime, and those two classes are connected with each other. The investigation of cyber terror requires high technology, system environment and experts, and general cyber crime is connected with general crime by evidence from digital data and cyber sp...

Pattern detection is one of the essential challenges in crime mapping and analysis. Data mining can be used to explore crime detection problems. A cluster technique is an effective method for determining areas with high concentrations of localized events. Conversely, it remains a particularly demanding task to detect hotspots with mapping methods in view of the vulnerability connected with the ...

Because of the use of computers and its advances in scientific data handling and advancement of various geo and space borne sensors, we are now faced with a large amount of data. Therefore, the development of new techniques and tools that support the transforming the data into useful knowledge has been the focus of the relatively new and interdisciplinary research area named “knowledge discover...

A common feature of mapped crime patterns is a strong spatial and temporal clustering into crime “hot spots”. In this paper we explore a social interaction model for the evolution of the attractiveness of the crime environment for criminal activity. We see how hot spots may arise when the idiosyncratic attractiveness of the environment is not encouraging for criminal activity. The stability of ...

This paper compares two variants of the Knox test in relation to space-time crime pattern analysis. A case study of H┌ヴェノ;ヴ┞ ;ミS けstolen-┗WエキIノWげ crime data sets of San Francisco city is presented. The comparative analysis shows that while one variant is designed to detect the sizes of the spatio-temporal neighbourhoods at which clustering (hotspots) is prominent within a data set, the other va...

s Crime is a behavior disorder that is an integrated result of social, economical and environmental factors. Crimes are a social nuisance and cost our society dearly in several ways. Any research that can help in solving crimes faster will pay for itself. In this paper we look at use of missing value and clustering algorithm for crime data using data mining. We will look at MV algorithm and Apr...

Data mining is vast field for mining knowledge in various fields of life. Crime mining is one of the applications focused here. Credit card and web based crime are increasingly as more technologies are rising high. To deal and overcome fraud clustering and classification techniques are implemented. Framework and process models are designed that provide user results, graphs and trees that help u...