Three Approaches to Client Email Topic Classification

Branislava Šandrih Todorović, Katarina Josipović, Jurij Kodre


Abstract
This paper describes a use case that was implemented and is currently running in production at the Nova Ljubljanska Banka, that involves classifying incoming client emails in the Slovenian language according to their topics and priorities. Since the proposed approach relies only on the Named Entity Recogniser (NER) of personal names as a language-dependent resource (for the purpose of anonymisation), that is the only prerequisite for applying the approach to any other language.
Anthology ID:
2023.ranlp-1.109
Volume:
Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
Month:
September
Year:
2023
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd., Shoumen, Bulgaria
Note:
Pages:
1015–1022
Language:
URL:
https://aclanthology.org/2023.ranlp-1.109
DOI:
Bibkey:
Cite (ACL):
Branislava Šandrih Todorović, Katarina Josipović, and Jurij Kodre. 2023. Three Approaches to Client Email Topic Classification. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 1015–1022, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.
Cite (Informal):
Three Approaches to Client Email Topic Classification (Šandrih Todorović et al., RANLP 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.ranlp-1.109.pdf