SigRA: A New Similarity Computation Method in Recommendation System

Because the collaborative filtering (CF) method has many advantages, it is widely used in recommendation systems. Measuring the similarity between users or items is an important step in collaborative filtering. The accuracy of existing similarity calculation methods should be improved. In this paper, we propose a new method for similarity calculation, which is called SigRA. This new method considers both the user's ratings of the items and the rated items by the users. Experiments on the MovieLens data set have been conducted using the proposed method, and the results are compared with that of several existing methods to verify the validity of the proposed method. Experimental results show that the proposed method is superior to the compared methods in terms of accuracy.