Hybrid Recommendation System Using Clustering and Collaborative Filtering

Abstract

A recommendation system is a way of suggesting users a subset of possible choice from a set of choices. An example of recommendation system in e-commerce web applications is to recommend customers what they might like to purchase from a wide variety of items based on their recent purchase behavior or search history. Recommender systems are redefining their meaning in today’s business oriented world by providing organizations an effective means of driving revenue. There are a lot of recommendation engines present at the moment. Some of them work solely on the user’s perspective whereas some work in generalized manner. There is a need that these recommender system start providing users with out of the box choices. They should not be limited to one’s individuality, rather other user preferences based on similarity should also be considered. Hence recommender systems play a major role in e-commerce domains and helps the business to achieve data intelligence. The proposed system explains various methods by which the user can be provided recommendations.