A Three-Dimensional Partial Weight Tensor Model for Teaching Recommendation

To address the problem that the teaching arrangements are not on the basis of recommendation in current school, a series of formalized methods are used to specify teachers' specialty foundation, course difficulty, and teaching evaluation first. Then, a kind of weighted function is defined to calculate the comprehensive partial weight for each group of teachers' professional foundation, course difficulty, and teaching evaluation. Next, the three-dimensional tensor model with partial weight is built on the 4-tuples relation of teacher-courseevaluation-weight and the comprehensive weight is endowed to the tensor elements. Finally, on the basis of above, a new kind of decomposition algorithm based on Tucker Decomposition is designed to obtain the approximate tensor of dimensionality reduction with the higher-order singular value decomposition (HOSVD), achieving the Top-N recommendation of teaching arrangements. Experiment results show that our proposed method can realize precise teaching arrangements recommendations when the iterative threshold value reaches a reasonable value, which can be used as a new intelligent recommendation method applied to the teaching arrangements in all kinds of schools.