Recommender System based on Food and Exercise Ontologies to Find the Suitable Fitness Exercise Plan with the Aid of Python

Abstract

In the modern world, professionals of diverse industrial sectors have severely become victims of Obese and Overweight conditions. Obese and Overweight conditions can be minimized by having proper dietary plans, physical activities and minimizing alcohol-based relaxation. In this research context, we try to address the issue of having poor physical exercise. We guide professionals with suitable exercises to reduce their weight in order to have the required Body Mass Index(BMI). The user body measurements that are recommended by the domain experts to concern such as sex, height, weight, exercise preferences, age, diet details and medical history used to calculate the degree of obesity of each individual. Then the degree of obesity is mapped with the knowledge base along with the predefined rules in order to match respective exercises suitable for the particular individuals that are compatible with the user’s medical history. Two ontologies for foods and exercises were developed using Protégé 4.3.0 and were retrieved by running Simple Protocol and Resource Description Framework Query Language (SPARQL) queries. Python 3 is used as the backend language for ontology and interface integration. Frontend developed using Tkinter GUI in Python 3 and is presented for the users to ease the interaction with the system. Two ontological files of Foods and Exercises are loaded and tested for consistency using the HermiT reasoner with the aid of Owlready2. Accuracy and Correctness are checked by addressing the competency questions and by domain experts’ inspections.