Application of Learning Data Sparse Coding Algorithm in Online English Guiding in the New Media Environment

Application of the learning data sparse coding algorithm in online English guiding in new media environment. This paper proposes an improved tracking algorithm based on the sparse coding representation model, which processes the tracking target into partial blocks and performs sparse coding on the partial blocks. By minimizing the objective function, the basic distribution difference from different modal data is reduced, and the similarity information between the same modal data is retained, and then, the system is implemented through the analysis of the new media integration. The system is implemented though the testing and the results are presented.