Research Article | OPEN ACCESS
Proposing a Framework for Exploration of Crime Data Using Web Structure and Content Mining
1Amin Shahraki Moghaddam, 2Javad Hosseinkhani, 2Suriayati Chuprat, 3Hamed Taherdoost and 4Hadi Barani Baravati
1Department of Computer, Zahedan Branch, Islamic Azad University, Zahedan, Iran
2Advanced Information School (AIS), Universiti Teknologi Malaysia (UTM),
Kuala Lumpur, Malaysia
3Deparment of Computer Engineering, Islamic Azad University, Semnan Branch, Semnan, Iran
4Department of Computer, Iranshahr Branch, Islamic Azad University, Iranshahr, Iran
Research Journal of Applied Sciences, Engineering and Technology 2013 19:3617-3624
Received: January 02, 2013 | Accepted: February 18, 2013 | Published: October 20, 2013
Abstract
The purpose of this study is to propose a framework and implement High-level architecture of a scalable universal crawler to maintenance the reliability gap and present the evaluation process of forensic data analysis criminal suspects. In Law enforcement agencies, criminal web data provide appropriate and anonymous information. Pieces of information implemented the digital data in the forensic analysis to accused social networks but the assessment of these information pieces is so difficult. In fact, the operator manually should pull out the suitable information from the text in the website and find the links and classify them into a database structure. In consequent, the set is ready to implement a various criminal network evaluation tools for testing. As a result, this procedure is not efficient because it has many errors and the quality of obtaining the analyzed data is based on the expertise and experience of the investigator subsequently the reliability of the tests is not constant. Therefore, the better result just comes from the knowledgeable operator. The objectives of this study is to show the process of investigating the criminal suspects of forensic data analysis to maintenance the reliability gap by proposing a structure and applying High-level architecture of a scalable universal crawler.
Keywords:
Crime web mining, criminal network, forensics analysis, framework, social network, terrorist network, universal crawler,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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