Data clustering is the concept of forming predefined number of clusters where the data points within each cluster are very similar to each other and the data points between clusters are dissimilar to each other. The concept of clustering is widely used in various domains like bioinformatics, medical data, imaging, marketing study and crime analysis. The popular types of clustering techniques ar...

Money-Laundering causes a higher prevalence of crime and reduces the desire tending to invest in productive activities. Also, it leads to weaken the integrity of financial markets and decrease government control over economic policy. Banks are able to prevent theft, fraud, money laundering conducted by customers through identification of their clients’ behavioral characteristics. This leads to ...

Crime reports clustering is crucial for identifying and preventing criminal activities that frequently happened in society. In the proposed work, named entities a report are recognized to extract crime-related phrases subsequently, preprocessed by applying stopword removal lemmatization operations. Next, module of universal encoder model, called transformer, applied get sentence embedding each ...

Recently digital forensics has become a prominent activity in crime investigation since computers are increasingly used as tools to commit crimes. During forensic investigation the digital devices such as desktops, notebooks, smart phones etc. found at the crime scene are collected for further investigation. Investigators have to go through humongous amount of data stored on these devices to ga...

One of the more popular approaches for the detection of crime hot spots is cluster analysis. Implemented in a wide variety of software packages, including CrimeStat, SPSS, SAS, and SPLUS, cluster analysis can be an effective method for determining areas exhibiting elevated concentrations of crime. However, it remains a particularly challenging task to detect hot spots using clustering technique...