Complaint Analysis and Classification for Economic and Food Safety
João Filgueiras, Luís Barbosa, Gil Rocha, Henrique Lopes Cardoso, Luís Paulo Reis, João Pedro Machado, Ana Maria Oliveira
Abstract
Governmental institutions are employing artificial intelligence techniques to deal with their specific problems and exploit their huge amounts of both structured and unstructured information. In particular, natural language processing and machine learning techniques are being used to process citizen feedback. In this paper, we report on the use of such techniques for analyzing and classifying complaints, in the context of the Portuguese Economic and Food Safety Authority. Grounded in its operational process, we address three different classification problems: target economic activity, implied infraction severity level, and institutional competence. We show promising results obtained using feature-based approaches and traditional classifiers, with accuracy scores above 70%, and analyze the shortcomings of our current results and avenues for further improvement, taking into account the intended use of our classifiers in helping human officers to cope with thousands of yearly complaints.- Anthology ID:
- D19-5107
- Volume:
- Proceedings of the Second Workshop on Economics and Natural Language Processing
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong
- Editors:
- Udo Hahn, Véronique Hoste, Zhu Zhang
- Venue:
- WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 51–60
- Language:
- URL:
- https://aclanthology.org/D19-5107
- DOI:
- 10.18653/v1/D19-5107
- Cite (ACL):
- João Filgueiras, Luís Barbosa, Gil Rocha, Henrique Lopes Cardoso, Luís Paulo Reis, João Pedro Machado, and Ana Maria Oliveira. 2019. Complaint Analysis and Classification for Economic and Food Safety. In Proceedings of the Second Workshop on Economics and Natural Language Processing, pages 51–60, Hong Kong. Association for Computational Linguistics.
- Cite (Informal):
- Complaint Analysis and Classification for Economic and Food Safety (Filgueiras et al., 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/D19-5107.pdf