Design of an ontology for detecting the social influence on non-communicable diseases risk factors
by Henrique Damasceno Vianna; Jorge Luis Victória Barbosa; João Carlos Gluz; Renan Belarmino Scherer Dos Santos
International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 13, No. 2, 2018

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.

Online publication date: Mon, 18-Mar-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Metadata, Semantics and Ontologies (IJMSO):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com