Mixed Recommendation Algorithm Based on Commodity Gene and Genetic Algorithm

摘要

To solve the problems of "new user" and "sparseness", we introduce the concept of commodity gene. Through coupling the commodity gene database, users' purchasing historical records, users' content of online browsing and the data of neighbors' behavior, we can form the module of candidate sets of customer preferences, and then use genetic algorithm which has been improved to make the selection and polymerization to the model, so that we can complete the best selection of neighbors. Finally, we can get the recommended sets according to the recommended module. Experimental results show that the algorithm we suggested can improve the accuracy of the recommendation and achieve good quality of recommendation.