Mining User's Data Based on Customer's Rating for Prediction and Recommendation-A Comparative Analysis

The business of E-commerce is increasingly becoming popular due to pervasive Internet technologies. It is a human tendency to rely on the data or information, which they receive from their friends and neighbours prior to taking any decision, especially before purchasing any item. Presently, people are getting vast information andworldwide data thoughWeb. Due to information overload, customers often face difficulties to locate their item of interest. Recommender system plays a significant role, and it helps to deal with information overload and further provides personalized recommendations to customers or users. In this paper, recommendation of smartphone was given based on feedback given by customer using weighted mean approach. The prediction was calculated for untried items, based on ratings given by new user using collaborative filtering. The results of recommendation and prediction show the approach is interesting.