Personalized Recommendation Based on Similarity of Cloud Model

Abstract

Analyzing the present situation of personalized recommendation system. Point out the limitation of similarity based on voting, and the disadvantage of the strict matching in calculating similarity. Put forward a new personalized recommendation method based on the statistics of item. Adopt the cloud model to calculate the similarity instead of traditional strict matching of cosine method. The experiments show that the system has better performance.