USING COMMUNITY DETECTION TECHNIQUE IN RECOMMENDER SYSTEM

Abstract

A BSTRACT . Recommender systems play a very important role in e-commerce sites. The goal of a recommender system is to predict the customer’s interest. Recommender systems are widely used to recommend products/items to the customers that are most relevant to their needs. Recommender systems make use of various data sources, in order to collect the characteristics of items, users, and their transactions. Traditional recommender systems have many issues which are still unresolved. Social network based recommender systems are based on communities. By forming user communities we can overcome problems of classical recommender systems and also enhance recommendations diversity. Finding communities is crucial because these communities in a network can help to classify users who share common interest. Community detection is one of the most active fields in complex networks which is used to find communities. This property can be used in various applications such as to study the spread of disease in social networks, product recommendation etc.