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Authors: 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 Sciences and Information Technologies, Slovenia

Keyword(s): Named-entity Linking, Knowledge Extraction, Dietary Recommendations, Computational Linguistics, Public Health.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Concept Mining ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: In order to help people to follow the new knowledge about healthy diet that comes rapidly each day with the new published scientific reports, a grammar and dictionary based named-entity linking method is presented that can be used for knowledge extraction of evidence-based dietary recommendations. The method consists of two phases. The first one is a mix of entity detection and determination of a set of candidates for each entity, and the second one is a candidate selection. We evaluate our method using a corpus from dietary recommendations presented in one sentence provided by the World Health Organization and the U.S. National Library of Medicine. The corpus consists of 50 dietary recommendations and 10 sentences that are not related with dietary recommendations. For 47 out of 50 dietary recommendations the proposed method extract all the useful knowledge, and for remaining 3 only the information for one entity is missing. Due to the 10 sentences that are not dietary recommendation the method does not extract any entities, as expected. (More)

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Paper citation in several formats:
Eftimov, T.; Koroušić Seljak, B. and Korošec, P. (2016). Grammar and Dictionary based Named-entity Linking for Knowledge Extraction of Evidence-based Dietary Recommendations. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR; ISBN 978-989-758-203-5; ISSN 2184-3228, SciTePress, pages 150-157. DOI: 10.5220/0006032401500157

@conference{kdir16,
author={Tome Eftimov. and Barbara {Koroušić Seljak}. and Peter Korošec.},
title={Grammar and Dictionary based Named-entity Linking for Knowledge Extraction of Evidence-based Dietary Recommendations},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR},
year={2016},
pages={150-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006032401500157},
isbn={978-989-758-203-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR
TI - Grammar and Dictionary based Named-entity Linking for Knowledge Extraction of Evidence-based Dietary Recommendations
SN - 978-989-758-203-5
IS - 2184-3228
AU - Eftimov, T.
AU - Koroušić Seljak, B.
AU - Korošec, P.
PY - 2016
SP - 150
EP - 157
DO - 10.5220/0006032401500157
PB - SciTePress