Visual Programming for Patent Mining

Saad, Farag; Aras, Hidir; Helfrich, Stefan

doi:10.34726/pst2019.7

Record link:

https://doi.org/10.34726/pst2019.7
http://hdl.handle.net/20.500.12708/828

Title:

Citation:

Saad, F., Aras, H., & Helfrich, S. (2019). Visual Programming for Patent Mining. 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/pst2019.7

reposiTUm DOI:

10.34726/pst2019.7

CatalogPlus:

AC15614475

Publication Type:

Inproceedings - Full-Paper Contribution

Language:

English

Authors:

Saad, Farag
Aras, Hidir
Helfrich, Stefan

Published in:

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

Date (published):

2019

Event name:

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

Event date:

12-Sep-2019

Event place:

Karlsruhe, Germany

Number of Pages:

Keywords:

Patent Mining; KNIME Analytics Platform; Workflows; Visual Programming; Hadoop; Scalability

Additional information:

In this paper we describe how to employ and extend the KNIME Analytics Platform with a Hadoop backend in order to realize scalable text mining workows for annotating and linking large-scale patent data.

License:

CC BY 4.0