SOCIAL NETWORK BASED OPINION PROCESSING FOR OPTIMAL RECOMMENDER ENGINE

In the latest trend of internet, optimized suggestions for the search are anticipated by every individual. Crowd sourcing, a largest human resource provider network useful in search suggestions that helps to find out common phrases that other people have searched for. We identify an interesting real time problem, finding the best products through suggestions with individual user rating to a particular brand as well as with the rating of the friends to the product and the generalized crowd sourcing opinion. The system comprise of product to product co-relation under a brand, user to user co- relation under common attributes, crowd sourcing opinion by means of key factors obtained for the product in order make the suggestions more optimal.