Research And Application Of The Collaborative Filtering Recommendation System Based On Cloud Computing

Along with the information increase on the Internet, people can easily get a lot of information. However, user find it’s difficult to find useful information for a limited time. Personalized recommendation is based on user’s interest to recommend, it can reduce the cost of the user to obtain useful information.Collaborative filtering recommendation technology is the most widely used and the most successful in personalized recommendation system by far. However, there are more and more data on the internet, and the data matrix is very thin, it makes the traditional collaborative filtering recommendation algorithm cost more time, lower the recommendation system’s real-time performance, reduces recommendation’s quality.1. Studied the basic principle of collaborative filtering recommendation algorithm, put forward design personalized movie recommendation system based on collaborative filtering recommendation algorithm. Studied the cloud computing, put forward using cloud computing to improve the real-time performance of collaborative filtering recommendation system.2. Design personalized movie recommendation system based on cloud computing, use Hadoop to build cloud platform, using Mahout Taste engine to develop movie recommendation system, using the GroupLens film data sets to test the system.