Discovering Criminal Networks by Web Structure Mining

Abstract

Constantly, criminal web data create new and appropriate information for Law implementation. In scientific analysis, the digital data comprises of some information of social networks suspicious. On the other hand, consider in the evaluation of these pieces of information, this issue is challenging issue. In fact, a detective has to pull out the useful information from the text in web pages manually. Then, also create a link between different pieces of information and classify them into an organized database. Additionally, the organized database is ready to utilize several criminal network assessment tools for evaluation. However, the process of manually organizing data for evaluation is not effective for the reason that it is likely to have many errors. Moreover, its reliability is not persistent because the quality of resulted assessed data depends on the practice and experience of the agent. Therefore, the more professional is an operator, the better objectives will be achieved. The aim of this study is to propose a framework which shows the process of exploring of the criminal suspects of scientific data assessments based on orders capable pages and links that are covering the reliability gap.

Authors:- Amin Shahraki Moghadam, Javad Hosseinkhani, Hamed Taherdoost and Vahid Golchinmehrabani

Keywords:- Crime Web Mining, Criminal Network, Forensics Analysis, Framework, Preferential Crawler, Social Network, Terrorist Network

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