Patent Retrieval : A Multi-Modal Visual Analytics Approach

Kurzanzeige
dc.contributor.authorSeebacher, Daniel
dc.contributor.authorStein, Manuel
dc.contributor.authorJanetzko, Halldor
dc.contributor.authorKeim, Daniel A.
dc.date.accessioned2017-01-24T11:36:03Z
dc.date.available2017-01-24T11:36:03Z
dc.date.issued2016eng
dc.description.abstractClaiming intellectual property for an invention by patents is a common way to protect ideas and technological advancements. However, patents allow only the protection of new ideas. Assessing the novelty of filed patent applications is a very time-consuming, yet crucial manual task. Current patent retrieval systems do not make use of all available data and do not explain the similarity between patents. We support patent officials by an enhanced Visual Analytics multi-modal patent retrieval system. Including various similarity measurements and incorporating user feedback, we are able to achieve significantly better query results than state-of-the-art methods.eng
dc.description.versionpublishedeng
dc.identifier.doi10.2312/eurova.20161118eng
dc.identifier.ppn1680794957
dc.identifier.urihttps://kops.uni-konstanz.de/handle/123456789/36920
dc.language.isoengeng
dc.rightsterms-of-use
dc.rights.urihttps://rightsstatements.org/page/InC/1.0/
dc.subjectPatent Retrieval, Visual Analyticseng
dc.subject.ddc004eng
dc.titlePatent Retrieval : A Multi-Modal Visual Analytics Approacheng
dc.typeINPROCEEDINGSeng
dspace.entity.typePublication
kops.citation.bibtex
@inproceedings{Seebacher2016Paten-36920,
  year={2016},
  doi={10.2312/eurova.20161118},
  title={Patent Retrieval : A Multi-Modal Visual Analytics Approach},
  isbn={978-3-03868-016-1},
  publisher={The Eurographics Association},
  booktitle={EuroVA16},
  editor={Natalia Andrienko and Michael Sedlmair},
  author={Seebacher, Daniel and Stein, Manuel and Janetzko, Halldor and Keim, Daniel A.},
  note={Article Number: 1118}
}
kops.citation.iso690SEEBACHER, Daniel, Manuel STEIN, Halldor JANETZKO, Daniel A. KEIM, 2016. Patent Retrieval : A Multi-Modal Visual Analytics Approach. EuroVA: International Workshop on Visual Analytics. Groningen, the Netherlands, 6. Juni 2016 - 10. Juni 2016. In: NATALIA ANDRIENKO, , ed., MICHAEL SEDLMAIR, ed.. EuroVA16. The Eurographics Association, 2016, 1118. ISBN 978-3-03868-016-1. Available under: doi: 10.2312/eurova.20161118deu
kops.citation.iso690SEEBACHER, Daniel, Manuel STEIN, Halldor JANETZKO, Daniel A. KEIM, 2016. Patent Retrieval : A Multi-Modal Visual Analytics Approach. EuroVA: International Workshop on Visual Analytics. Groningen, the Netherlands, Jun 6, 2016 - Jun 10, 2016. In: NATALIA ANDRIENKO, , ed., MICHAEL SEDLMAIR, ed.. EuroVA16. The Eurographics Association, 2016, 1118. ISBN 978-3-03868-016-1. Available under: doi: 10.2312/eurova.20161118eng
kops.citation.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/123456789/36920">
    <dc:contributor>Stein, Manuel</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-01-24T11:36:03Z</dcterms:available>
    <dcterms:title>Patent Retrieval : A Multi-Modal Visual Analytics Approach</dcterms:title>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/36920/1/Seebacher_2-5ub10vls1u6r0.pdf"/>
    <dcterms:abstract xml:lang="eng">Claiming intellectual property for an invention by patents is a common way to protect ideas and technological advancements. However, patents allow only the protection of new ideas. Assessing the novelty of filed patent applications is a very time-consuming, yet crucial manual task. Current patent retrieval systems do not make use of all available data and do not explain the similarity between patents. We support patent officials by an enhanced Visual Analytics multi-modal patent retrieval system. Including various similarity measurements and incorporating user feedback, we are able to achieve significantly better query results than state-of-the-art methods.</dcterms:abstract>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2017-01-24T11:36:03Z</dc:date>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/36920/1/Seebacher_2-5ub10vls1u6r0.pdf"/>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dc:rights>terms-of-use</dc:rights>
    <dc:creator>Stein, Manuel</dc:creator>
    <dc:contributor>Janetzko, Halldor</dc:contributor>
    <dc:language>eng</dc:language>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Seebacher, Daniel</dc:contributor>
    <dc:creator>Janetzko, Halldor</dc:creator>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dcterms:issued>2016</dcterms:issued>
    <dc:creator>Seebacher, Daniel</dc:creator>
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/36920"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
  </rdf:Description>
</rdf:RDF>
kops.conferencefieldEuroVA: International Workshop on Visual Analytics, 6. Juni 2016 - 10. Juni 2016, Groningen, the Netherlandsdeu
kops.date.conferenceEnd2016-06-10eng
kops.date.conferenceStart2016-06-06eng
kops.description.openAccessopenaccessgreen
kops.flag.knbibliographytrue
kops.identifier.nbnurn:nbn:de:bsz:352-2-5ub10vls1u6r0
kops.location.conferenceGroningen, the Netherlandseng
kops.sourcefieldNATALIA ANDRIENKO, , ed., MICHAEL SEDLMAIR, ed.. <i>EuroVA16</i>. The Eurographics Association, 2016, 1118. ISBN 978-3-03868-016-1. Available under: doi: 10.2312/eurova.20161118deu
kops.sourcefield.plainNATALIA ANDRIENKO, , ed., MICHAEL SEDLMAIR, ed.. EuroVA16. The Eurographics Association, 2016, 1118. ISBN 978-3-03868-016-1. Available under: doi: 10.2312/eurova.20161118deu
kops.sourcefield.plainNATALIA ANDRIENKO, , ed., MICHAEL SEDLMAIR, ed.. EuroVA16. The Eurographics Association, 2016, 1118. ISBN 978-3-03868-016-1. Available under: doi: 10.2312/eurova.20161118eng
kops.title.conferenceEuroVA: International Workshop on Visual Analyticseng
relation.isAuthorOfPublicationc447972b-d42f-4fb1-8448-80f5d44dbd22
relation.isAuthorOfPublication12232899-556b-423f-a0b5-2e7c32fc1e07
relation.isAuthorOfPublication3d0e691c-3386-4127-8c0e-608e9b72a19f
relation.isAuthorOfPublicationda7dafb0-6003-4fd4-803c-11e1e72d621a
relation.isAuthorOfPublication.latestForDiscoveryc447972b-d42f-4fb1-8448-80f5d44dbd22
source.bibliographicInfo.articleNumber1118eng
source.contributor.editorNatalia Andrienko
source.contributor.editorMichael Sedlmair
source.identifier.isbn978-3-03868-016-1eng
source.publisherThe Eurographics Associationeng
source.titleEuroVA16eng

Dateien

Originalbündel

Gerade angezeigt 1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
Seebacher_2-5ub10vls1u6r0.pdf
Größe:
174.71 KB
Format:
Adobe Portable Document Format
Beschreibung:
Seebacher_2-5ub10vls1u6r0.pdf
Seebacher_2-5ub10vls1u6r0.pdfGröße: 174.71 KBDownloads: 388

Sammlungen

Informatik und Informationswissenschaft: Publikationen