Abstract
In this paper we present the main components of a weekly diet report generator (DRG) in natural language. The idea is to produce a text that contains information on the adherence of the dishes eaten during a week to the Mediterranean diet. The system is based on a user model, a database of the dishes eaten during the week and on the automatic computation of the Mediterranean Diet Score. All these sources of information are exploited to produce a highly personalized text. The system has two main goals, related to two different kinds of users: on the one hand, when used by dietitians, the main goal is to highlight the most salient medical information of the patient diet and, on the other hand, when used by final users, the main goal is to educate them toward a Mediterranean style of eating.- Anthology ID:
- 2022.nlg4health-1.5
- Volume:
- Proceedings of the First Workshop on Natural Language Generation in Healthcare
- Month:
- July
- Year:
- 2022
- Address:
- Waterville, Maine, USA and virtual meeting
- Editors:
- Emiel Krahmer, Kathy McCoy, Ehud Reiter
- Venue:
- NLG4Health
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 40–45
- Language:
- URL:
- https://aclanthology.org/2022.nlg4health-1.5
- DOI:
- Cite (ACL):
- Elena Monfroglio, Lucas Anselma, and Alessandro Mazzei. 2022. Personalizing Weekly Diet Reports. In Proceedings of the First Workshop on Natural Language Generation in Healthcare, pages 40–45, Waterville, Maine, USA and virtual meeting. Association for Computational Linguistics.
- Cite (Informal):
- Personalizing Weekly Diet Reports (Monfroglio et al., NLG4Health 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.nlg4health-1.5.pdf