Analysis of Criminal Profiling Utilizing Structured and Unstructured Data

In general, the structured data knows the meaning of the sentence and unstructured data refers to an unknown means. Although the quantity of structured information in the entire data and within organizations is increasing, the majority of information remains available only in unstructured data. While different in form, both unstructured and structured information sources provide information about entities in the world and their properties and relations. Due to the recent rapid changes in society and wide spread of information devices, diverse digital information is utilized in a variety of economic and social analysis. Information related to the crime statistics by type of crime has been used as a major factor in crime. However, statistical analysis using only the structured data has the difficulty in the investigation by providing limited information to investigators and users. In this paper, structured data and unstructured data are analyzed by applying Korean Natural Language Processing (Ko-NLP) and the Latent Semantic Analysis (LSA) technique. It will provide a crime profile optimum system that can be applied to the crime profiling system or statistical analysis