Recurrent Tensor Factorization for time-aware service recommendation

Yiwen Zhang, Chunhui Yin, Zhihui Lu, Dengcheng Yan, Meikang Qiu, Qifeng Tang

Abstract: Highlights•A novel deep learning based method is proposed for time-aware service recommendation.•Two sub-methods are developed to collaboratively work on embedding dense vectors.•A hybrid loss function is designed to prevent unbalanced fitting problem.•Experiments indicate that our proposed method outperforms six state-of-the-art methods.