Contribution to a conference collection:
Interactive Visualization and Feature Transformation for Multidimensional Data Projection

No Thumbnail Available
Date
2013
relationships.isEditorOf
Contact
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
URI (citable link)
ArXiv-ID
International patent number
Link to the license
Project
EU project number
Open Access publication
Restricted until
Title in another language
Research Projects
Organizational Units
Journal Issue
Publication type
Contribution to a conference collection
Publication status
Abstract
Projecting multidimensional data to a lower-dimensional visual display as a scatter-plot-like visualization is a common approach for analyzing multidimensional data. Many dimension reduction techniques exist for performing such a task, but the quality of projections varies in terms of both preserving the original data structure and avoiding cluttered visual displays. In this paper, we propose an interactive feature transformation approach that allows the analyst to monitor and improve the projection quality by transforming feature space and assessing/ comparing the quality of different projection results. The method integrates feature selection and transformation as well as a variety of projection quality measures to help analyst generate uncluttered projections that preserve the structural properties of the data. These projections enhance the visual analysis process and provide a better understanding of data.
Summary in another language
Subject (DDC)
004 Computer Science
Keywords
Published in
EuroVis Workshop on Visual Analytics using Multidimensional Projections / Aupetit, M.; van der Maaten, L. (ed.). - Goslar : Eurographics, 2013. - pp. 21-25. - ISBN 978-3-905674-53-8
Conference
EuroVis, Jun 19, 2013, Leipzig, Germany
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690PÉREZ, Daniel, Leishi ZHANG, Matthias SCHÄFER, Tobias SCHRECK, Daniel A. KEIM, Ignacio DÍAZ, 2013. Interactive Visualization and Feature Transformation for Multidimensional Data Projection. EuroVis. Leipzig, Germany, Jun 19, 2013. In: AUPETIT, M., ed., L. VAN DER MAATEN, ed.. EuroVis Workshop on Visual Analytics using Multidimensional Projections. Goslar:Eurographics, pp. 21-25. ISBN 978-3-905674-53-8. Available under: doi: 10.2312/PE.VAMP.VAMP2013.021-025
BibTex
@inproceedings{Perez2013Inter-24914,
  year={2013},
  doi={10.2312/PE.VAMP.VAMP2013.021-025},
  title={Interactive Visualization and Feature Transformation for Multidimensional Data Projection},
  isbn={978-3-905674-53-8},
  publisher={Eurographics},
  address={Goslar},
  booktitle={EuroVis Workshop on Visual Analytics using Multidimensional Projections},
  pages={21--25},
  editor={Aupetit, M. and van der Maaten, L.},
  author={Pérez, Daniel and Zhang, Leishi and Schäfer, Matthias and Schreck, Tobias and Keim, Daniel A. and Díaz, Ignacio}
}
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/123456789/24914">
    <dcterms:bibliographicCitation>EuroVis Workshop on Visual Analytics using Multidimensional Projections ; June 19, 2013, Leipzig, Germany / M. Aupetit and L. van der Maaten. - Goslar: Eurographics, 2013. - S. 21-25. - ISBN 978-3-905674-53-8</dcterms:bibliographicCitation>
    <dc:contributor>Zhang, Leishi</dc:contributor>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dcterms:issued>2013</dcterms:issued>
    <dc:creator>Schreck, Tobias</dc:creator>
    <dcterms:title>Interactive Visualization and Feature Transformation for Multidimensional Data Projection</dcterms:title>
    <dc:contributor>Schäfer, Matthias</dc:contributor>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/24914/2/Perez_249148.pdf"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-06-30T22:25:05Z</dcterms:available>
    <dc:contributor>Díaz, Ignacio</dc:contributor>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:creator>Zhang, Leishi</dc:creator>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/24914/2/Perez_249148.pdf"/>
    <dc:creator>Schäfer, Matthias</dc:creator>
    <dc:contributor>Schreck, Tobias</dc:contributor>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24914"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:creator>Díaz, Ignacio</dc:creator>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:rights>terms-of-use</dc:rights>
    <dc:language>eng</dc:language>
    <dc:creator>Pérez, Daniel</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dc:contributor>Pérez, Daniel</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-11-06T09:39:33Z</dc:date>
    <dcterms:abstract xml:lang="eng">Projecting multidimensional data to a lower-dimensional visual display as a scatter-plot-like visualization is a common approach for analyzing multidimensional data. Many dimension reduction techniques exist for performing such a task, but the quality of projections varies in terms of both preserving the original data structure and avoiding cluttered visual displays. In this paper, we propose an interactive feature transformation approach that allows the analyst to monitor and improve the projection quality by transforming feature space and assessing/ comparing the quality of different projection results. The method integrates feature selection and transformation as well as a variety of projection quality measures to help analyst generate uncluttered projections that preserve the structural properties of the data. These projections enhance the visual analysis process and provide a better understanding of data.</dcterms:abstract>
  </rdf:Description>
</rdf:RDF>
Internal note
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Contact
URL of original publication
Test date of URL
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
Refereed
Link to research data
Description of supplementary data