DC Field
Value
Language
dc.contributor.author
Arts, Sam
-
dc.contributor.author
Hou, Jianan
-
dc.contributor.author
Gomez, Juan Charlos
-
dc.date.accessioned
2020-06-27T18:05:33Z
-
dc.date.issued
2019
-
dc.identifier.citation
<div class="csl-bib-body"> <div class="csl-entry">Arts, S., Hou, J., &#38; Gomez, J. C. (2019). Text Mining to Measure Novelty and Diffusion of Technological Inventions. In <i>Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)</i>. 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019), Karlsruhe, Germany. https://doi.org/10.34726/pst2019.2</div> </div>
-
dc.identifier.uri
https://doi.org/10.34726/pst2019.2
-
dc.identifier.uri
http://hdl.handle.net/20.500.12708/833
-
dc.description
Traditional measures of patent novelty and diffusion mostly rely on patent classification or citation information. Given that inventive ideas are embedded in the text of patent documents, our study validates different alternative natural language processing techniques to measure the novelty and diffusion of technological inventions. As a validation test, we collect a set of patents linked to famous awards such as the Nobel prize. Overall, text-based measures outperform other commonly-used novelty and diffusion metrics.
-
dc.language
English
-
dc.language.iso
en
-
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
-
dc.subject
patent
en
dc.subject
text
en
dc.subject
natural language processing
en
dc.subject
novelty
en
dc.subject
impact
en
dc.subject
indicator
en
dc.title
Text Mining to Measure Novelty and Diffusion of Technological Inventions
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.identifier.doi
10.34726/pst2019.2
-
dc.rights.holder
Authors 2019
-
dc.type.category
Full-Paper Contribution
-
dc.publisher.place
Karlsruhe, Germany
-
tuw.booktitle
Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)
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tuw.version
vor
-
dc.identifier.libraryid
AC15614218
-
dc.description.numberOfPages
2
-
dc.identifier.urn
urn:nbn:at:at-ubtuw:3-9413
-
dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
tuw.event.name
1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)
-
tuw.event.startdate
12-09-2019
-
tuw.event.enddate
12-09-2019
-
tuw.event.online
On Site
-
tuw.event.type
Event for scientific audience
-
tuw.event.place
Karlsruhe
-
tuw.event.country
DE
-
tuw.event.presenter
Arts, Sam
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item.languageiso639-1
en
-
item.openairetype
conference paper
-
item.grantfulltext
open
-
item.fulltext
with Fulltext
-
item.cerifentitytype
Publications
-
item.openairecristype
http://purl.org/coar/resource_type/c_5794
-
item.openaccessfulltext
Open Access
-
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