@misc{10481/86008,
year = {2020},
url = {https://hdl.handle.net/10481/86008},
abstract = {This paper addresses the problem of mapping equivalent
items between two databases based on their textual descriptions. Specif-
ically, we will apply this technique to link the elements of two food com-
position databases by calculating the most likely match of each item
in another given database. A number of experiments have been carried
by employing different distance metrics, some of them involving Fuzzy
Logic. The experiments show that the mappings are highly accurate and
Fuzzy Logic improves the precision of the model.},
organization = {European Union under grant
agreement No. 816303 (Stance4Health)},
publisher = {Springer Nature},
keywords = {Word embedding},
keywords = {Fuzzy distance},
keywords = {Database alignment},
title = {A Word Embedding Model for Mapping Food Composition Databases Using Fuzzy Logic},
doi = {https://doi.org/10.1007/978-3-030-50143-3_50},
author = {Morales Garzón, Andrea and Gómez Romero, Juan and Martín Bautista, María José},
}