Applying Data Science to Criminal Intelligence Analysis

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Date
2017
Authors
Qazi, Nadeem
Blomqvist, Eva
Aichroth, Patrick
Weigel, Christian
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VALCRI White Paper Series; VALCRI-WP-2017-003
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Open Access publication
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Informatik und Informationswissenschaft
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Working Paper/Technical Report
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Abstract
A major challenge of criminal intelligence analysis is to process large amount of semi-structured or unstructured data such as textual documents and videos and to extract useful information out of the data to support semantic search, sense-making and decision making. In VALCI, a computational framework is developed that incorporates concept extraction, ontology use and evolution, associative search, and image/ video analysis for semantic search and knowledge discovery. In this whitepaper we introduce the key concepts have been applied and their corresponding technologies that have been developed to tackle the challenge.
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Subject (DDC)
004 Computer Science
Keywords
Criminal Intelligence, Semantic Search, Evolving Knowledge Base, Ontology, Associative Search, Concept Extraction, Video Analysis
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ISO 690QAZI, Nadeem, Leishi ZHANG, Eva BLOMQVIST, Florian STOFFEL, Patrick AICHROTH, Christian WEIGEL, 2017. Applying Data Science to Criminal Intelligence Analysis
BibTex
@techreport{Qazi2017Apply-45078,
  year={2017},
  series={VALCRI White Paper Series},
  title={Applying Data Science to Criminal Intelligence Analysis},
  number={VALCRI-WP-2017-003},
  url={http://valcri.org/valcri/applying-data-science-to-criminal-intelligence-analysis/},
  author={Qazi, Nadeem and Zhang, Leishi and Blomqvist, Eva and Stoffel, Florian and Aichroth, Patrick and Weigel, Christian}
}
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http://valcri.org/valcri/applying-data-science-to-criminal-intelligence-analysis/
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2019-02-18
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