Visual Comparative Case Analytics

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SACHA, Dominik, Wolfgang JENTNER, Leishi ZHANG, Florian STOFFEL, Geoffrey ELLIS, 2017. Visual Comparative Case Analytics. EuroVA17 : EuroVis Workshop on Visual Analytics. Barcelona, Spain, Jun 12, 2017 - Jun 13, 2017. In: SEDLMAIR, Michael, ed., Christian TOMINSKI, ed.. EuroVA17 : EuroVis Workshop on Visual Analytics : proceedings. Goslar:The Eurographics Association, pp. 49-54. ISBN 978-3-03868-042-0. Available under: doi: 10.2312/eurova.20171119

@inproceedings{Sacha2017Visua-41265, title={Visual Comparative Case Analytics}, year={2017}, doi={10.2312/eurova.20171119}, isbn={978-3-03868-042-0}, address={Goslar}, publisher={The Eurographics Association}, booktitle={EuroVA17 : EuroVis Workshop on Visual Analytics : proceedings}, pages={49--54}, editor={Sedlmair, Michael and Tominski, Christian}, author={Sacha, Dominik and Jentner, Wolfgang and Zhang, Leishi and Stoffel, Florian and Ellis, Geoffrey} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:creator>Sacha, Dominik</dc:creator> <dc:creator>Zhang, Leishi</dc:creator> <dc:creator>Stoffel, Florian</dc:creator> <dc:contributor>Stoffel, Florian</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:title>Visual Comparative Case Analytics</dcterms:title> <bibo:uri rdf:resource=""/> <dc:contributor>Jentner, Wolfgang</dc:contributor> <dc:contributor>Zhang, Leishi</dc:contributor> <dc:language>eng</dc:language> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Sacha, Dominik</dc:contributor> <dc:contributor>Ellis, Geoffrey</dc:contributor> <dcterms:issued>2017</dcterms:issued> <dcterms:available rdf:datatype="">2018-02-07T15:54:26Z</dcterms:available> <dc:creator>Jentner, Wolfgang</dc:creator> <dcterms:isPartOf rdf:resource=""/> <dcterms:abstract xml:lang="eng">Criminal Intelligence Analysis (CIA) faces a challenging task in handling high-dimensional data that needs to be investigated with complex analytical processes. State-of-the-art crime analysis tools do not fully support interactive data exploration and fall short of computational transparency in terms of revealing alternative results. In this paper we report our ongoing research into providing the analysts with such a transparent and interactive system for exploring similarities between crime cases. The system implements a computational pipeline together with a visual platform that allows the analysts to interact with each stage of the analysis process and to validate the result. The proposed Visual Analytics (VA) workflow iteratively supports the interpretation of obtained clustering results, the development of alternative models, as well as cluster verification. The visualizations offer a usable way for the analyst to provide feedback to the system and to observe the impact of their interactions.</dcterms:abstract> <dc:date rdf:datatype="">2018-02-07T15:54:26Z</dc:date> <dspace:isPartOfCollection rdf:resource=""/> <dc:creator>Ellis, Geoffrey</dc:creator> </rdf:Description> </rdf:RDF>

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