HYBRID RECOMMENDATION SYSTEM BASED UPON NETWORK

Abstract

In today world large number of people uses internet. People always connected to internet through their gadgets (smartphone, pads and laptops). Due to advancement in communication technology, internet available at low cost which lead people always online or connected to internet. So activity such as online shopping, searching, social interaction etc. increase over internet with exponential rate. As a result more online data is available about users. Ecommerce industry uses these available data to suggest their items to customers. They develops recommendation system. These recommendation systems increase their sells. Also provide new platform to customer for comparing and refer similar items. Now days thousands of products available in market. Most of people confused between products, which products best or most appropriate for them. Recommendation systems also helps them to compare products based upon similarity and dissimilarity. Enable customer to select best appropriate product according to their requirement. Recommendation system also able to handle ambiguous query posted by user and varied user profile. Therefore, help in reducing information load by considered only selected items based upon input query. They targeted to deliver specific information to the specific user. Recommendation process basically based on classification and clustering methods. They are usually hidden from end user, delivered them high quality information which enhance user satisfaction and performance of system.