Ontology-based intelligent multi-agent for diet food recommendation

K.Prakash, R.Sivakumar Abstract— A healthy diet and lifestyle are the most effective approaches to prevent disease. When a person eats too much or too little on a continual basis, the risk of disease will increase. Therefore, developing healthy and balanced eating habits is essential to disease prevention. This study proposes an intelligent diet food recommendation multi-agent (IDFRMA), including a personal profile agent, a nutrition facts analysis agent, a knowledge analysis agent, a discovery agent, a fuzzy inference agent, and a semantic generation agent for healthy diet planning. The IDFRMA provides a semantic analysis of healthy diet status for people based on the preconstructed ontology by domains experts and results of fuzzy inference. With the generated semantic analysis, people can get healthy information about what they eat and make it easier to eat a balanced and healthy diet. The experimental platform has been constructed to test the performance of the IDFRMA. The results indicate that the IDFRMA can effectively work for healthy diet planning.