Persistent Link:
http://hdl.handle.net/10150/105157
Title:
Using Coplink to Analyze Criminal-Justice Data
Author:
Hauck, Roslin V.; Atabakhsh, Homa; Ongvasith, Pichai; Gupta, Harsh; Chen, Hsinchun
Citation:
Using Coplink to Analyze Criminal-Justice Data 2002-03, 35:30-37 Computer
Publisher:
IEEE
Journal:
Computer
Issue Date:
Mar-2002
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105157
Submitted date:
2004-08-16
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
Keywords:
Web Mining; Knowledge Management; World Wide Web
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab; CopLink

Full metadata record

DC FieldValue Language
dc.contributor.authorHauck, Roslin V.en_US
dc.contributor.authorAtabakhsh, Homaen_US
dc.contributor.authorOngvasith, Pichaien_US
dc.contributor.authorGupta, Harshen_US
dc.contributor.authorChen, Hsinchunen_US
dc.date.accessioned2004-08-16T00:00:01Z-
dc.date.available2010-06-18T23:20:21Z-
dc.date.issued2002-03en_US
dc.date.submitted2004-08-16en_US
dc.identifier.citationUsing Coplink to Analyze Criminal-Justice Data 2002-03, 35:30-37 Computeren_US
dc.identifier.urihttp://hdl.handle.net/10150/105157-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractAs 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectWeb Miningen_US
dc.subjectKnowledge Managementen_US
dc.subjectWorld Wide Weben_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherCopLinken_US
dc.titleUsing Coplink to Analyze Criminal-Justice Dataen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalComputeren_US
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