Design recommendation system in e-commerce site


In recent years it has spread the used of e-commerce sites quite dramatically. Thus, these sites have become display huge number of diverse products. It became difficulty for the customer to choose what he/she wants from this product. The recommender systems are used to help customers to finding the desired product of their interests and proved to be an important solution to information overload problem. This paper, designed a recommendation system based on content, which is usually textual description. Furthermore, the proposed system uses cosine similarity function to find the similarities among the characteristics of various products, and nominate a suitable product closer to customer satisfaction. The experimental result shows that the proposed system can provide suitable product with accuracy up to 95%.