Recently several recommender systems have been developed in a variety of applications，but providing accurate recommendations that match the preferences and constraints of various users is quite challenging. This paper presents a method of recommending digital products based on the past preference of a user on the price， rating and selling v이니me of a product. Experimental results of the method with actual data of Amazon showed that the average accuracy of the recommendations made by the method is 85%. Although the results are preliminary，the method is potentially capable of making more accurate personalized recommendations than existing methods.