A Hybrid Approach for Design and Implementation of Web Based Recommender System

Abstract

Recommender System (RS) has the ability to predict and recommend the future preferences for the user. Due to the Internet availability and its large connected user base, users now have enormous possibilities to select from. As the amount of information is massively increasing daily it is difficult for the user to filter the relevant and useful information. The problem of information overload is dealt through the use of recommender system that speeds up the user search and provide the content that is relevant and according to their interest resulting in newlineenhanced user experience. In the past, shopping was done from physical stores where the user choice was limited by the number of items available in the store. By contrast, today the Internet allows people to access abundant resources online. Websites like Amazon, Netflix has enormous collection of items for the user to opt from. With the increase in the available information the users find it difficult to select the data they want to actually see. The aim of the newlineRecommender System is to predict and recommend items based on the user interests. In order to boost their sales E-commerce and retail companies are implementing recommender systems.Through personalized offers generated by the system the companies are boosting their sales, gaining and retaining customers by knowing their needs and surprising them with offers they never thought of. In addition to increased sales and profits, including recommendation in their systems the companies are gaining a competitive advantage newline