电子科技大学学报2017，Vol.46Issue(5)：747-754,8.DOI:10.3969/j.issn.1001-0548.2017.05.018
三维有偏权值张量分解在授课推荐上的应用研究
A Three-Dimensional Partial Weight Tensor Model for Teaching Recommendation
摘要
Abstract
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-course-evaluation-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.关键词
数据规约/授课推荐/张量分解/三维有偏权值张量Key words
data reduction/teaching recommendation/tensor decomposition/three-dimensional partial weighted tensor分类
信息技术与安全科学引用本文复制引用
姚敦红,李石君,胡亚慧..三维有偏权值张量分解在授课推荐上的应用研究[J].电子科技大学学报,2017,46(5):747-754,8.基金项目
国家自然科学基金(61272109) （61272109）
湖南省教育厅科学研究项目(15C1086) （15C1086）
