Efficiency Booster Techniques for Recommendation System

Recommendation Systems (RS) work as guides, it is guiding users to find products of their interest. It’s a fact that with the increase in RS deployment, traditional methods need modifications. Many techniques and different approaches have been developed to generate an effective recommendation. This is interesting as different application’s scenarios could have a fittest solution. This article throws light on techniques to turn the traditional methods more useful for real-world scenario to boost the productivity of RS. Finally, proposed a similarity fusion method for increasing efficiency of a recommendation system.