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- 2017
三维有偏权值张量分解在授课推荐上的应用研究
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Abstract:
为解决现今学校授课安排无推荐依据这一实际问题，首先给出了一系列形式化方法用于规约教师的专业基础、课程难度及教学评价；定义了一种加权函数计算出每组专业基础、课程难度和教学评价的综合有偏权值；构建了一种基于“教师-课程-评价-权值”四元关系的三维有偏权值张量模型，张量元素使用综合有偏权值。在此基础上，设计了一种基于Tucker分解的算法，对张量进行高阶奇异值分解（HOSVD）得到降维后的近似张量，按课程分类实现了Top_N授课推荐。实验结果表明，当迭代阈值达到一个合理值时，该方法能实现精准授课推荐，可作为一种新的智能化授课推荐方法应用于各类学校。
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