Criminal Investigation

Abstract

Datamining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science. The whole goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw study step, it involves database and data management aspects, data pre-processing, model and inference thoughts, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating Data mining is the analysis step of the knowledge discovery in databases" process. Their relationships with criminals. The high volume of crime datasets and also the complexity of relationships between these kinds of data have made criminology an appropriate field for applying data mining techniques. Identifying crime characteristics is the first step for developing further analysis. The knowledge that is gained from data mining approaches is a very useful tool which can help and support police forces. An approach based on data mining techniques is discussed in this paper to extract important entities police narrative reports which are written in plain text. By using this approach, crime data can be automatically entered into a database, in law enforcement agencies. We have also applied a SOM clustering method in the scope of crime analysis and finally we will use the clustering results in order to perform crime matching process.