Paper Title
Keyword Based Recommender System for Electronic products using weight Based Recommendation Algorithm implemented on Hadoop

Abstract
Recommender system is a topic which falls under the domain of information retrieval, data mining and machine learning. Recommender systems are widely used by famous websites like Amazon, Flipcart, Netflix, Facebook, twitter and many others. There are various types of recommender systems like collaborative filtering, content based filtering and hybrid recommender system. Recommender systems can be used for recommending various products like books, movies, music and any products in general. Various researchers uptil now have developed various algorithms to improve the accuracy of recommender systems and provide good quality recommendations. Algorithm and approach used determines the quality of recommendations. In this paper we are proposing a keyword based recommender system for recommending electronic products. We recommend the products based on keywords. We are using weight based recommendation approach. Since we are taking into account the previous user preferences it also falls under the category of user based collaborative filtering. Recommender system also needs to handle big data. So in order to provide scalability we are implementing it in Hadoop using mapreduce . We have implemented the product using java and the database used is mysql. The integrated development environment used is Netbeans IDE 8.0.2 Index terms: information retrieval, data mining, machine learning, collaborative filtering, content based filtering, hybrid recommendersystem,keyword based recommendation, weight based recommendation, big data, hadoop, mapreduce, java, mysql