loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Gordana Ispirova 1 ; Tome Eftimov 1 ; Barbara Koroušić Seljak 2 and Peter Korošec 3

Affiliations: 1 Jožef Stefan Institute and Jožef Stefan International Postgraduate School, Slovenia ; 2 Jožef Stefan Institute, Slovenia ; 3 Jožef Stefan Institute, Faculty of Mathematics and Natural Science and Information Technologies, Slovenia

Keyword(s): Semantic Web, Food Domain Ontology, Food Composition Data, Text Similarity, Text Normalization.

Related Ontology Subjects/Areas/Topics: Applications and Case-studies ; Artificial Intelligence ; Collaboration and e-Services ; Domain Analysis and Modeling ; e-Business ; Enterprise Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Ontology Sharing and Reuse ; Semantic Web ; Soft Computing ; Symbolic Systems

Abstract: Food composition data are detailed sets of information on food components, providing values for energy and nutrients, food classifiers and descriptors. The data of this kind is presented in food composition databases, which are a powerful source of knowledge. Food composition databases may differ in their structure between countries, which makes it difficult to connect them and preferably compare them in order to borrow missing values. In this paper, we present a method for mapping food composition data from various sources to a terminological resource-a food domain ontology. An existing ontology used for the mapping was extended and modelled to cover a larger portion of the food domain. The method was evaluated on two food composition databases: EuroFIR and USDA.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.191.171.72

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Ispirova, G. ; Eftimov, T. ; Koroušić Seljak, B. and Korošec, P. (2017). Mapping Food Composition Data from Various Data Sources to a Domain-Specific Ontology. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD; ISBN 978-989-758-272-1; ISSN 2184-3228, SciTePress, pages 203-210. DOI: 10.5220/0006504302030210

@conference{keod17,
author={Gordana Ispirova and Tome Eftimov and Barbara {Koroušić Seljak} and Peter Korošec},
title={Mapping Food Composition Data from Various Data Sources to a Domain-Specific Ontology},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD},
year={2017},
pages={203-210},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006504302030210},
isbn={978-989-758-272-1},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KEOD
TI - Mapping Food Composition Data from Various Data Sources to a Domain-Specific Ontology
SN - 978-989-758-272-1
IS - 2184-3228
AU - Ispirova, G.
AU - Eftimov, T.
AU - Koroušić Seljak, B.
AU - Korošec, P.
PY - 2017
SP - 203
EP - 210
DO - 10.5220/0006504302030210
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic