Enhancing Peoples' Training Experience: A Gym Workout Planner Based on Soft Ontologies

摘要

The development of novel interactive systems for supporting our daily activities (e.g., gym training activities) demands flexible and dynamic ontologies for knowledge representation and application support. In this paper, we propose a soft ontology-based architecture for dealing with decision support and recommendation under dynamic and uncertainty situations, including those related to gym training activities. Our architecture considers users' characteristics and group's feedback (e.g., comments, evaluation, sensor data and results) to develop and evolve flexible ontological structures using a Fuzzy RDF approach for implementing soft ontologies. The architecture was implemented by the OntoGymWP application, which provides suggestions of gym workout plans based on users' features and social feedback represented in Fuzzy RDF ontologies. These ontologies are used to semantically encode: users' profile; shared concepts from the domain for each group of users; and training plans for each individual. The implemented proof of concept reveals the viability of the architecture, as well as its potentiality in providing suitable gym workout plans based on extensible and flexible ontologies.