Model-based Collaborative Filtering using Refined K-Means and Genetic Algorithm

As cloud computing has emerged as new computing paradigm, more and more web services has been provided on the Internet, thereby how to select a qualified service is becoming a key issue. Several approaches based on Clustering, e.g., K-Means (KMC) Clustering, Fuzzy clustering, Subtractive Clustering has been proposed. KMC is a popular clustering algorithm based on the partition of data. However, it has some limitations, such as its requiring a user to give out the number of clusters at first, and its sensitiveness to initial conditions, and second it can only find linearly separable clusters. In this paper, we have proposed a new context known as Refined K-Means Clustering (KMC) and Genetic Algorithm. Refined KMC is an extension of standard KMC to solve the limitations of standard KMC and provide recommendation. Genetic Algorithm is used to improve the cluster quality than standard KMC and Refined KMC.