Collaborative Recommender System for Online Book Retailing by using Associative Rule Mining Approach

Abstract

Recommender systems help the users to find and evaluate items of interest. They connect user with items to consume by associating the opinions of other individuals with the consuming user’s actions or opinions. Such system has become powerful tool in e-commerce sites to facilitate the buying process. In this paper, we present the application of recommender system for online book retailing. We use a hybrid model of Association Rule Mining approach to find the frequent book-itemsets and Collaborative filtering techniques to generate recommendations base on the past buying behavior of the consumers and the items in the rules observed by association rule mining approach. We use the Apriori algorithm as the underlying techniques of association rule mining approach.