Content Extraction and Lexical Analysis from Customer-Agent Interactions

Sergiu Nisioi, Anca Bucur, Liviu P. Dinu


Abstract
In this paper, we provide a lexical comparative analysis of the vocabulary used by customers and agents in an Enterprise Resource Planning (ERP) environment and a potential solution to clean the data and extract relevant content for NLP. As a result, we demonstrate that the actual vocabulary for the language that prevails in the ERP conversations is highly divergent from the standardized dictionary and further different from general language usage as extracted from the Common Crawl corpus. Moreover, in specific business communication circumstances, where it is expected to observe a high usage of standardized language, code switching and non-standard expression are predominant, emphasizing once more the discrepancy between the day-to-day use of language and the standardized one.
Anthology ID:
W18-6118
Volume:
Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
Venue:
WNUT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
132–136
Language:
URL:
https://aclanthology.org/W18-6118
DOI:
10.18653/v1/W18-6118
Bibkey:
Cite (ACL):
Sergiu Nisioi, Anca Bucur, and Liviu P. Dinu. 2018. Content Extraction and Lexical Analysis from Customer-Agent Interactions. In Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, pages 132–136, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Content Extraction and Lexical Analysis from Customer-Agent Interactions (Nisioi et al., WNUT 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/improve-issue-templates/W18-6118.pdf