Jihong Ding

TL;DR: A novel multivariate multi-order Markov transition to realize multi-modal accurate predictions and experimental results demonstrate that the proposed SJE based approach can improve the prediction accuracy for network traffic by highest up to 38.47 percentage points compared with the Z-eigen based approach.

TL;DR: Experimental results based on real-world GPS trajectory dataset demonstrate that TT-HODED algorithm can significantly improve the computation efficiency and reduce the running memory on the premise of guaranteeing the almost consistent prediction accuracy compared to the original H ODED algorithm.

TL;DR: Cloud computing is introduced to the construction of the digital learning environment for its on-demand services with high reliability, scalability and availability in the distributed environment and the experimental results demonstrate that the co-construction and sharing model and incentive mechanism of DLECC may provide meaningful learning support and interactive communities.

TL;DR: This article aims to provide sustainable smart educational services including precise personalized recommendation and adaptive clustering under different contexts by correlatively analyzing the global educational data from multiple dimensions via incremental tensor decomposition.

TL;DR: Wang et al. as mentioned in this paper proposed a series of tensor-based RNNs and a T-RNNs based multi-modal prediction approach (TMMP) to provide accurate prediction services.