Towards the healthy nutritional dietary patterns

Association rule mining is a popular technique in data mining and it has an extremely wide application area. In this paper, we study the association rule mining problem and propose a cascaded approach to extract the interesting healthy nutritional dietary patterns. Our approach is mainly based on the Apriori algorithm and rule deduction techniques. To test the feasibility and effectiveness of the new approach, we conduct series of experiments with the data obtained from the U. S. Department of Agriculture Food and Nutrient Database for Dietary Studies 3.0. Our experimental results demonstrate that the proposed approach can successfully extract many interesting healthy nutritional dietary patterns. Also some important patterns are unknown before.