Detecting Suspicion Information on the Web Using Crime Data Mining Techniques

Along with the rapid popularity of the Internet, crime information on the web is becoming increasingly rampant, and the majority of them are in the form of text. Because a lot of crime information in documents is described through events, event-based semantic technology can be used to study the patterns and trends of web-oriented crimes. The purpose of this paper is to provide a review to mining useful information by means of Data Mining. The procedure of extracting knowledge and information from large set of data is data mining that applying artificial intelligence method to find unseen relationships of data. There is more study on data mining applications that attracted more researcher attention and one of the crucial field is criminology that applying in data mining which is utilized for identifying crime characteristics. Detecting and exploring crimes and investigating their relationship with criminals are involved in the analyzing crime process. Criminology is a suitable field for using data mining techniques that shows the high volume and the complexity of relationships between crime datasets. Therefore, for further analysis development, the identifying crime characteristic will be the first step and obtained knowledge from data mining approaches is a very useful tool to help and support police forces. This research aims to provide a review to extract Detecting Suspicion Information on the Web using Crime Data Mining Techniques Javad Hosseinkhani, Mohammad Koochakzaei, Solmaz keikhaee, and Javid Hosseinkhani Naniz Copyright © 2014 Helvetic Editions LTD All Rights Reserved www.elvedit.com 33 useful information by means of Data Mining, in order to find crime hot spots out and predict crime trends for them using crime data mining techniques.

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