Text Mining to Measure Novelty and Diffusion of Technological Inventions

Arts, Sam; Hou, Jianan; Gomez, Juan Charlos

doi:10.34726/pst2019.2

Datensatz Zitierlink:

https://doi.org/10.34726/pst2019.2
http://hdl.handle.net/20.500.12708/833

Titel:

Text Mining to Measure Novelty and Diffusion of Technological Inventions

Zitat:

Arts, S., Hou, J., & Gomez, J. C. (2019). Text Mining to Measure Novelty and Diffusion of Technological Inventions. In Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019). 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019), Karlsruhe, Germany. https://doi.org/10.34726/pst2019.2

reposiTUm-DOI:

10.34726/pst2019.2

CatalogPlus:

AC15614218

Publikationstyp:

Konferenzbeitrag - Full-Paper Contribution

Sprache:

Englisch

Autor_innen:

Arts, Sam
Hou, Jianan
Gomez, Juan Charlos

Erschienen in:

Proceedings of The 1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)

Datum (veröffentlicht):

2019

Veranstaltungsname:

1st Workshop on Patent Text Mining and Semantic Technologies (PatentSemTech 2019)

Veranstaltungszeitraum:

12-Sep-2019

Veranstaltungsort:

Karlsruhe, Deutschland

Umfang:

Keywords:

patent; text; natural language processing; novelty; impact; indicator

Weitere Information:

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.

Lizenz:

CC BY 4.0