KOPS - The Institutional Repository of the University of Konstanz

Combining automated analysis and visualization techniques for effective exploration of high-dimensional data

Combining automated analysis and visualization techniques for effective exploration of high-dimensional data

Cite This

Files in this item

Checksum: MD5:f22f0fb649bde1cffdb7deceb14172ee

TATU, Andrada, Georgia ALBUQUERQUE, Martin EISEMANN, Jörn SCHNEIDEWIND, Holger THEISEL, Marcus MAGNOR, Daniel A. KEIM, 2009. Combining automated analysis and visualization techniques for effective exploration of high-dimensional data. 2009 IEEE Symposium on Visual Analytics Science and Technology. Atlantic City, NJ, USA, Oct 12, 2009 - Oct 13, 2009. In: 2009 IEEE Symposium on Visual Analytics Science and Technology. IEEE, pp. 59-66. ISBN 978-1-4244-5283-5. Available under: doi: 10.1109/VAST.2009.5332628

@inproceedings{Tatu2009-10Combi-5750, title={Combining automated analysis and visualization techniques for effective exploration of high-dimensional data}, year={2009}, doi={10.1109/VAST.2009.5332628}, isbn={978-1-4244-5283-5}, publisher={IEEE}, booktitle={2009 IEEE Symposium on Visual Analytics Science and Technology}, pages={59--66}, author={Tatu, Andrada and Albuquerque, Georgia and Eisemann, Martin and Schneidewind, Jörn and Theisel, Holger and Magnor, Marcus and Keim, Daniel A.} }

<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/rdf/resource/123456789/5750"> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5750"/> <dc:creator>Magnor, Marcus</dc:creator> <dcterms:rights rdf:resource="https://kops.uni-konstanz.de/page/termsofuse"/> <dc:language>eng</dc:language> <dcterms:title>Combining automated analysis and visualization techniques for effective exploration of high-dimensional data</dcterms:title> <dc:contributor>Theisel, Holger</dc:contributor> <dc:creator>Theisel, Holger</dc:creator> <dc:contributor>Albuquerque, Georgia</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:59:48Z</dc:date> <dcterms:abstract xml:lang="eng">Visual exploration of multivariate data typically requires projection onto lower dimensional representations. The number of possible representations grows rapidly with the number of dimensions, and manual exploration quickly becomes ineffective or even unfeasible. This paper proposes automatic analysis methods to extract potentially relevant visual structures from a set of candidate visualizations. Based on features, the visualizations are ranked in accordance with a specified user task. The user is provided with a manageable number of potentially useful candidate visualizations, which can be used as a starting point for interactive data analysis. This can effectively ease the task of finding truly useful visualizations and potentially speed up the data exploration task. In this paper, we present ranking measures for class-based as well as non class-based Scatterplots and Parallel Coordinates visualizations. The proposed analysis methods are evaluated on different datasets.</dcterms:abstract> <dc:contributor>Schneidewind, Jörn</dc:contributor> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5750/1/Tatu_2009_CombiningAutomated.pdf"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Eisemann, Martin</dc:creator> <dcterms:bibliographicCitation>First publ. in: IEEE Symposium on Visual Analytics Science and Technology (VAST) : Atlantic City, New Jersey, USA, October 12-13, 2009 : proceedings / John Stasko. - [Piscataway, N.J.] : IEEE Xplore, 2009. - pp. 59-66. - ISBN 978-1-4244-5283-5</dcterms:bibliographicCitation> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Tatu, Andrada</dc:contributor> <dc:contributor>Eisemann, Martin</dc:contributor> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:creator>Schneidewind, Jörn</dc:creator> <dc:contributor>Magnor, Marcus</dc:contributor> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:59:48Z</dcterms:available> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dc:format>application/pdf</dc:format> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/rdf/resource/123456789/36"/> <dcterms:issued>2009-10</dcterms:issued> <dc:creator>Tatu, Andrada</dc:creator> <dc:creator>Keim, Daniel A.</dc:creator> <dc:rights>terms-of-use</dc:rights> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5750/1/Tatu_2009_CombiningAutomated.pdf"/> <dc:creator>Albuquerque, Georgia</dc:creator> </rdf:Description> </rdf:RDF>

Downloads since Oct 1, 2014 (Information about access statistics)

Tatu_2009_CombiningAutomated.pdf 738

This item appears in the following Collection(s)

Search KOPS


Browse

My Account