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    Using Coplink to Analyze Criminal-Justice Data

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    Author
    Hauck, Roslin V.
    Atabakhsh, Homa
    Ongvasith, Pichai
    Gupta, Harsh
    Chen, Hsinchun
    Issue Date
    2002-03
    Submitted date
    2004-08-16
    Keywords
    Web Mining
    Knowledge Management
    World Wide Web
    Local subject classification
    National Science Digital Library
    NSDL
    Artificial intelligence lab
    AI lab
    CopLink
    
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    Show full item record
    Citation
    Using Coplink to Analyze Criminal-Justice Data 2002-03, 35:30-37 Computer
    Publisher
    IEEE
    Journal
    Computer
    Description
    Artificial Intelligence Lab, Department of MIS, University of Arizona
    URI
    http://hdl.handle.net/10150/105157
    Abstract
    As information technologies and applications become more overwhelming and diverse, persistent information overload problems have become ever more urgent.1 Fallout from this trend has most affected government, specifically criminaljustice information systems. The explosive growth in the digital information maintained in the data repositories of federal, state, and local criminal-justice entities and the spiraling need for cross-agency access to that information have made utilizing it both increasingly urgent and increasingly difficult. The Coplink system applies a concept spaceâ a statistics-based, algorithmic technique that identifies relationships between suspects, victims, and other pertinent dataâ to accelerate criminal investigations and enhance law enforcement efforts.
    Type
    Journal Article (Paginated)
    Language
    en
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