Hybrid Recommendation System with Collaborative Filtering and Association Rule Mining Using Big Data

The large amount of increase in information available over the Internet has created a greatest challenge in searching useful information. As a result an intelligent approach such as recommendation system is used that can recommend everything from movies, books, music, restaurant, news and jokes that can efficiently retrieve useful information from web. Collaborative filtering is primary approach of any RS. But only CF cannot provide enough scalability and accuracy. This paper presents a model that combines RS method such as CF with big data technique such as association rule mining. The main focus of this paper is to provide a scalable and robust recommendation system that can provide good accuracy. In our work, we have proposed conduction of a personalized movie recommendation by considering user's past behavior.