Product Recommendation using Machine Learning

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems – content-based recommending and collaborative filtering (CF). This study focuses on improving the performance of recommender systems by using data mining techniques. This paper proposes an SVM based recommender system. We conducted an experiment to evaluate the proposed model on the each type of product data set such as Grocery, Beauty, Cold drinks, watches, lockers, Gourmet Foods etc. and compared them with the traditional algorithm. The results show the proposed model is improvement in making recommendations.