Recommendation systems mean based on customers interest techniques and tools are to generate the new products and services. The main issue in this recommendation system is the number of users are more and giving preference to their items takes more time. And also processing the date takes more time. Hence, clustering techniques are used for users into overlapping groups helps in the information sparsely issue and improve recommendation range. Next essential factor in this system is dynamic attention on users in which their importance varies. This work mainly concentrates on using the ant clustering technique to improvethe multi-view clustering method.
P.Latchoumi et al. (Sun,) studied this question.