The Development Of The Personalized Intelligent Recommendation System

With the rapid development of e-commerce and the great advances of data mining technology, the recommendation service becomes more and more popular. The aim of the recommendation system is to help customers find a product which suits them best from a great amount of goods information, thus saving considerable time for users and improving their experience.A personalized intelligent recommendation system on diet is designed, which is mainly to recommend a suitable healthy diet menu to users through related regulations based on users’ physical and previous diet preference. The system sets relevant healthy attribute of each dish and tracks users’ attention items. When users log in, the system will test the users’ physical fitness first and then judge their diet preference according to their previous diet habits. In the end, the system obtains an intelligent recommendation about dishes based on the uses’ physical and preference attribute.The association algorithm adopted in this system is based on the analysis of the classical Apriori algorithm, and optimize its defects while judging users’ diet preference. The optimized algorithm only needs to query database twice. For the first time, it finds out and analyses candidate 1-itemset, and then lists all the possible k-itemset. For the second time, it finds out the support degree of all the itemset, and then obtain the final itemset through comparison and analysis. The query times and the generation of frequent itemset is reduced because of the optimized algorithm, thus the algorithm efficiency is improved. Compared with the classical Apriori algorithm in the same case, the advantages of the improved algorithm on mining efficiency has been proved. At last, the new algorithm is used to this personalized intelligent diet recommendation system. With the analysis of the dishes’ attribute concerned by users, it excavates the users’ dietary preferences in the course of diet. Thereby, it brings about the development of the recommendation system of the personalized diet which is connected with Traditional Chinese Medicine.