A Context-aware Collaborative Filtering Algorithm on Mobile Recommendation

Towards the problem of personalized recommendation in mobile network,presented a collaborative filtering algorithm based on context similarity of users by incorporating users' context information into collaborative filtering recommendation process. The algorithm calculates firstly context similarities to construct a set of similar contexts related to the current context of the user. Using context pre-filtering recommentation method,the "useritem-context"3D model is reduced to the "user-item"2D model. Finally,it predicts the unknown user preferences and generates recommendations based on Slope one algorithm. Experimental results indicate that this algorithm achieve better recommendation accuracy than the traditional CF algorithm and Slope one algorithm.