International Journal for Innovative Research in Science and Technology (IJIRST)
Today people are living in an era of big data. Large numbers of services are available to customers; from these services it is difficult for them to choose those that are most appropriate for them. In this scenario a wide variety of service recommender systems will guide the user in selecting the most appropriate one. But these traditional service recommender systems will not work well with big data environment; they will experience scalability and efficiency problems as it has to work on huge amount of data. Most of the existing recommender system will provide same rating and ranking of services to different customers.