Design of an ontology for detecting the social influence on non-communicable diseases risk factors. (2018)

• Record Type: Journal Article
• Authors: Vianna, Henrique Damasceno; Barbosa, Jorge Luis Victoria; Gluz, João Carlos; Santos, Renan Belarmino Scherer Dos
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 13:Number 2(2018)
• Page Start: 120
• Page End: 130
• Publication Date: 2018
• Subjects: ontology -- ontology engineering -- chronic diseases -- non-communicable diseases -- social influence -- social networks; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

Non-communicable diseases are caused by habits such as poor diets, lack of physical activity practice or smoking. Besides, some studies have already correlated the influence of social relations on some factors of these diseases like weight gain, feeling of happiness and quitting smoking. This paper presents the design of an ontology for detecting the social influence on the spreading of non-communicable diseases risk factors following Gruniger and Fox's methodology. Its motivation scenario focuses on the recommendation of beneficial connections to social network members. UML was used to represent domain and range of object properties, data properties, and subsumption, while the Manchester syntax was used to demonstrate equivalences. To test the ontology a small social network was created using axioms from the ontology in PROLOG and defining the necessary conditions for the ontology to suggest new connections for a node to obtain a lower probability of obesity.