Publikation:

Patent Retrieval : A Multi-Modal Visual Analytics Approach

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2016

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URI (zitierfähiger Link)
http://nbn-resolving.de/urn:nbn:de:bsz:352-2-5ub10vls1u6r0
DOI (zitierfähiger Link)
https://doi.org/10.2312/eurova.20161118
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Open Access Green

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Informatik und Informationswissenschaft: Publikationen
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Beitrag zu einem Konferenzband
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Published

Erschienen 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.20161118

Zusammenfassung

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.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
004 Informatik

Schlagwörter

Patent Retrieval, Visual Analytics

Konferenz

EuroVA: International Workshop on Visual Analytics, 6. Juni 2016 - 10. Juni 2016, Groningen, the Netherlands
Rezension
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Zitieren

ISO 690SEEBACHER, 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.20161118
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}
}
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