A Service Recommendation System Based on Rough Multidimensional Matrix in Cloud-Based Environment.

In order to efficiently and accurately realize the service recommend to cloud-based environment, a collaborative filtering algorithm using rough decision mechanism in handling the uncertainty is established. We proposed a service recommendation system in cloud-based environment that helps a user to select the best services from different cloud providers that match user requirements. The new system combines items' attributes information (decision tags) and user's attribute information (decision times), achieves high performance and alleviates the cold-start problems of recommendation systems. A rough multidimensional matrix model based on cooperative filtering algorithm is proposed. Specifically, we design useful selection criteria based on items' attributes and users' attributes, and combine the criteria in an optimization framework of cloud-based environment. Experiments show that this method can effectively solve the cold start problem of new projects, and is more accurate than the traditional collaborative filtering algorithm.