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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/3913
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| タイトル: | Detecting Terrorist Activity Patterns Using Investigative Data Mining Tool |
| 著者: | Nasrullah, Memon |
| キーワード: | Investigative Data Mining
iMiner
terrorist networks
visualization
social network analysis |
| 発行日: | Nov-2005 |
| 出版者: | JAIST Press |
| 抄録: | Law enforcement agencies across the globe have begun to focus on innovative knowledge discovery technologies to aid in the analysis of terrorists’ information. The use of such technologies serves as intelligence tools to combat terrorism by predicting terrorism activity. As opposed to traditional data mining aiming at extracting knowledge form data, mining for investigative analysis, called Investigative Data Mining (IDM), aims at discovering hidden instances of patterns of interest, such as patterns indicating an organized crime activity. An important problem targeted by IDM is identification of terrorist networks, based on available intelligence. We present an approach to an IDM solution of this problem, using semantic link analysis and visualization of findings. The approach is demonstrated in an application by a prototype system. The system finds associations between terrorist and terrorist organizations and is capable of determining links between terrorism plots occurred in the past, their affiliation with terrorist camps, travel record, and funds transfer, etc. The findings are represented by a network in the form of an attributed relational graph (ARG). Paths from a node to any other node in the network indicate the relationships between individuals and organizations. The system also provides assistance to law enforcement agencies, indicating when the capture of a specific terrorist will likely destabilize the terrorist network. In this paper we discuss this important application area, relate it to existing database technology and suggest how this technology should be extended to provide more appropriate facilities. We describe what we regard as an important new type of approaches, i.e. subgraph retrieval facilities, and present a demonstrator that we have implemented. |
| 記述: | The original publication is available at JAIST Press http://www.jaist.ac.jp/library/jaist-press/index.html
IFSR 2005 : Proceedings of the First World Congress of the International Federation for Systems Research : The New Roles of Systems Sciences For a Knowledge-based Society : Nov. 14-17, 2123, Kobe, Japan
Symposium 5, Session 3 : Data/Text Mining from Large Databases Data Mining |
| 言語: | ENG |
| URI: | http://hdl.handle.net/10119/3913 |
| ISBN: | 4-903092-02-X |
| 出現コレクション: | IFSR 2005
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このアイテムのファイル:
| ファイル |
記述 |
サイズ | 形式 |
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| 20164.pdf | | 144Kb | Adobe PDF | 見る/開く |
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