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In order to solve the user rating data about data sparseness and traditional similarity calculation method because of its disadvantages of strict match object attributes, combined with the project classification and cloud computing platform is put forward an improved collaborative filtering recommendation algorithm. The experimental results show that the algorithm not only effectively solve the data sparse and the insufficiency of traditional similarity method, but also improved the user's interests and the accuracy of the nearest neighbor search; At the same time, the algorithm only need to calculate where new users or categories, greatly enhance the scalability of the system. Keywords-data is sparse; cloud computing; collaborative filtering recommendation algorithm

Research and Application of Collaborative Filtering Algorithm Based on Hadoop