Comparison of Named Entity Recognition Methods on Real-World and Highly Imbalanced Business Document Datasets

Moreno-Acevedo SA, Escobar-Grisales D, Vasquez-Correa JC, Orozco Arroyave JR (2022)

Publication Type: Conference contribution

Publication year: 2022

Journal

Communications in Computer and Information Science Springer Verlag

Publisher: SPRINGER INTERNATIONAL PUBLISHING AG

City/Town: CHAM

Pages Range: 41-53

Conference Proceedings Title: APPLIED COMPUTER SCIENCES IN ENGINEERING, WEA 2022

Event location: Bogota CO

DOI: 10.1007/978-3-031-20611-5_4

Authors with CRIS profile

Juan Rafael Orozco Arroyave Professur für Informatik (Mustererkennung)

Involved external institutions

Universidad de Antioquía (UDEA) CO Colombia (CO)

How to cite

APA:

Moreno-Acevedo, S.A., Escobar-Grisales, D., Vasquez-Correa, J.C., & Orozco Arroyave, J.R. (2022). Comparison of Named Entity Recognition Methods on Real-World and Highly Imbalanced Business Document Datasets. In APPLIED COMPUTER SCIENCES IN ENGINEERING, WEA 2022 (pp. 41-53). Bogota, CO: CHAM: SPRINGER INTERNATIONAL PUBLISHING AG.

MLA:

Moreno-Acevedo, S. A., et al. "Comparison of Named Entity Recognition Methods on Real-World and Highly Imbalanced Business Document Datasets." Proceedings of the 9th Workshop on Engineering Applications (WEA), Bogota CHAM: SPRINGER INTERNATIONAL PUBLISHING AG, 2022. 41-53.

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