文章基本信息

标题：Criminal Communities Mining on the Web
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作者：Javad Hosseinkhani ; Suriayati Chuprat ; Hamed Taherdoost 等
期刊名称：International Journal of Advanced Computer Science and Information Technology
电子版ISSN：2296-1739
出版年度：2013
卷号：2
期号：2
页码：10
语种：English
出版社：Helvetic Editions
摘要：Criminal web data always offer novel and useful knowledge and information for Law administration. The used digital data in legal assessments are involved parts of information about the accused’ social networks. Thus, evaluation of these parts of information is challenging. Therefore, an investigator has to pull out the appropriate information from the text manually, these information are on the website. An investigator also makes the relationship between various parts of information and classify them in to a structured database so the category is ready to use in different criminal network evaluation tools for analysis. On the other hand, these manual processes are not adequate in the case that it has many errors. Moreover, as the quality of resulted evaluation depends on the investigator’s proficiency, the reliability is not stable. On another word, the more proficient operator, the better result achieved. The purpose of this paper is suggesting a framework by using concurrent crawler to show the process of exploring the criminal accused of legal data evaluation which insures the reliability gap.