(untitled) (International Journal of Engineering and Computer Science, 2013)
Recommender systems is becomes popular and used in many fields for gathering the information based on the user requirements. It is mainly used to help the user for accessing the process based on the relevant information. Many framework for recommendation systems based on the different algorithms are revolve around the concept of accuracy only but other important feature such as diversity of the recommendations are unnoticed. In this paper efficient optimization technique along with the novel ranking technique is proposed for providing more diverse recommendations by satisfying the requirements recommendation features. The proposed algorithm is compared with the existing item based ranking technique and simulated with many real world data sets.