Authors:
Tome Eftimov
1
;
Gordana Ispirova
2
;
Paul Finglas
3
;
Peter Korošec
4
and
Barbara Koroušić Seljak
1
Affiliations:
1
Computer Systems Department, Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana and Slovenia
;
2
Computer Systems Department, Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia, Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000 Ljubljana and Slovenia
;
3
Quadram Institute Bioscience, Norwich research Park, Norwich, Norfolk, NR4 7UA and U.K.
;
4
Computer Systems Department, Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia, Faculty of Mathematics, Natural Sciences and Information Technologies, Glagoljaška ulica 8, 6000 Koper and Slovenia
Keyword(s):
E-health, Ontology Learning, Part of Speech Tagging, Personalized Dietary Web Service, Semantic Web, String Similarity.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Data Engineering
;
Domain Analysis and Modeling
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Symbolic Systems
Abstract:
Unhealthy diet can lead to diseases such as diabetes, allergies, and some types of cancer, among other health-related problems. In order to help users and clinical dietitians access the relevant knowledge about food and nutrition data in e-health systems that use different data sources, ontologies about food and related domains, such as clinical medicine, individual user profile, etc., are very important in providing successful and smart e-health systems. In this paper we present an ontology-learning process using personalized dietary web services that are dealing with food-related data and knowledge rules. The result of the ontology-learning process is an OWL ontology that is developed in a semi-automatic way and can be used for the harmonization of personalized dietary web services and will enable researchers to share information in this domain. In addition, it can also use aggregated data from different sources to provide new knowledge and help people live healthier lives.