Research on the personalization recommendation of mobile business based on the ant colony optimization algorithm

In this paper, we prompt a new method of personalization recommendation of mobile business based on the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a heuristic algorithm which has been proven a successful technique and applied to a number of combinatorial optimization (CO) problems. To solve the problems of scalability and sparsity in the collaborative filtering, this paper proposed a personalization recommendation algorithm based on rough set is proposed The algorithm refine the user ratings data usin, dimensionality reduction, then uses a new similarity measurf to find the target users’ neighbors, and then generate! recommendations. To prove our algorithm's effectiveness, the authors conduct experiments on the public dataset. Theoretical analysis and experimental results show that this method is efficient and effective. © 2016, UK Simulation Society. All rights reserved.