Applying Data Science to Criminal Intelligence Analysis
Applying Data Science to Criminal Intelligence Analysis
No Thumbnail Available
Files
There are no files associated with this item.
Date
2017
Authors
Editors
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
VALCRI White Paper Series; VALCRI-WP-2017-003
International patent number
Link to the license
oops
EU project number
Project
Open Access publication
Collections
Title in another language
Publication type
Working Paper/Technical Report
Publication status
Published
Published in
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.
Summary in another language
Subject (DDC)
004 Computer Science
Keywords
Criminal Intelligence, Semantic Search, Evolving Knowledge Base, Ontology, Associative Search, Concept Extraction, Video Analysis
Conference
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690
QAZI, Nadeem, Leishi ZHANG, Eva BLOMQVIST, Florian STOFFEL, Patrick AICHROTH, Christian WEIGEL, 2017. Applying Data Science to Criminal Intelligence AnalysisBibTex
@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} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/45078"> <dc:contributor>Blomqvist, Eva</dc:contributor> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dcterms:abstract xml:lang="eng">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.</dcterms:abstract> <dc:creator>Zhang, Leishi</dc:creator> <dc:creator>Weigel, Christian</dc:creator> <dc:contributor>Aichroth, Patrick</dc:contributor> <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/45078"/> <dc:contributor>Weigel, Christian</dc:contributor> <dc:contributor>Qazi, Nadeem</dc:contributor> <dc:creator>Qazi, Nadeem</dc:creator> <dc:creator>Blomqvist, Eva</dc:creator> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:language>eng</dc:language> <dc:creator>Stoffel, Florian</dc:creator> <dcterms:issued>2017</dcterms:issued> <dc:contributor>Stoffel, Florian</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-02-18T14:43:28Z</dc:date> <dcterms:title>Applying Data Science to Criminal Intelligence Analysis</dcterms:title> <dc:contributor>Zhang, Leishi</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:creator>Aichroth, Patrick</dc:creator> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-02-18T14:43:28Z</dcterms:available> </rdf:Description> </rdf:RDF>
Internal note
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
URL of original publication
Test date of URL
2019-02-18
Examination date of dissertation
Method of financing
Comment on publication
Alliance license
Corresponding Authors der Uni Konstanz vorhanden
International Co-Authors
Bibliography of Konstanz
Yes