Dish Classification using Knowledge based Dietary Conflict Detection

Nadia Clairet

[How to correct problems with metadata yourself]


Abstract
The present paper considers the problem of dietary conflict detection from dish titles. The proposed method explores the semantics associated with the dish title in order to discover a certain or possible incompatibility of a particular dish with a particular diet. Dish titles are parts of the elusive and metaphoric gastronomy language, their processing can be viewed as a combination of short text and domain-specific texts analysis. We build our algorithm on the basis of a common knowledge lexical semantic network and show how such network can be used for domain specific short text processing.
Anthology ID:
R17-2001
Volume:
Proceedings of the Student Research Workshop Associated with RANLP 2017
Month:
September
Year:
2017
Address:
Varna
Editors:
Venelin Kovatchev, Irina Temnikova, Pepa Gencheva, Yasen Kiprov, Ivelina Nikolova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
1–9
Language:
URL:
https://doi.org/10.26615/issn.1314-9156.2017_001
DOI:
10.26615/issn.1314-9156.2017_001
Bibkey:
Cite (ACL):
Nadia Clairet. 2017. Dish Classification using Knowledge based Dietary Conflict Detection. In Proceedings of the Student Research Workshop Associated with RANLP 2017, pages 1–9, Varna. INCOMA Ltd..
Cite (Informal):
Dish Classification using Knowledge based Dietary Conflict Detection (Clairet, RANLP 2017)
Copy Citation:
PDF:
https://doi.org/10.26615/issn.1314-9156.2017_001