Web data mining discovers valuable information or knowledge from the web hyperlink structure, page content and usage data. Along with the swift popularity of the Internet, crime information on the web is becoming increasingly flourishing, and the majority of them are in the form of text. A major challenge facing all law-enforcement and intelligence-gathering organizations is accurately and efficiently analyzing the growing volumes of crime data. Detecting, exploring crimes and investigating their relationship with criminals are a big challenge to the present world. The evaluation of the different dimensions of widespread criminal web data causes one of the research challenges to the researchers. Criminal web data always offer convenient and applicable information for law administration and intelligence department. The goal of crime data mining is to understand patterns in criminal behavior in order to predict crime anticipate criminal activity and stop it. This paper describes web data mining which includes structure mining, web content mining, web usage mining and crime data mining. The occurrences of criminal activities based on web data mining process is also presented in this paper. The presented information on different criminal activities can be used to reduce further occurrences of similar incidence and to stop the crime.
Keywords: Classification, Clustering., Crime Control., Crime data, Pattern Analysis, Web Mining
