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A Collaborative Filtering Recommendation Algorithm Based on Cloud Model

Recommendation system is one of the most important technologies applied in e-commerce. Similarity measuring method is fundamental to collaborative filtering algorithm, and traditional methods are inefficient especially when the user rating data are extremely sparse. Based on the outstanding characteristics of Cloud Model on the process of transforming a qualitative concept to a set of quantitative numerical values, a novel similarity measuring method, namely the likeness comparing method based on cloud model (LICM) is proposed in this paper. LICM compares the similarity of two users on knowledge level, which can overcome the drawback of attributes' strictly matching. This work analysis traditional methods throughly and puts forward a novel collaborative filtering algorithm, which is based on the LICM method. Experiments on typical data set show the excellent performance of the present collaborative filtering algorithm based on LICM, even with extremely sparsity of data.