计算机科学
正规化(语言学)
选择(遗传算法)
推荐系统
课程(导航)
集合(抽象数据类型)
期限(时间)
组分(热力学)
机器学习
数据挖掘
人工智能
天文
量子力学
热力学
物理
程序设计语言
作者
Jinjiao Lin,Haitao Pu,Yibin Li,Jian Lian
标识
DOI:10.1016/j.procs.2018.03.023
摘要
Being an essential component of smart education, we propose a novel recommendationsystem for course selection in the specialty of information management inChinese Universities.To implement this system, we firstly collect the course enrollment data-set for specific group of students. The sparse linear method (SLIM) is introduced in our framework to generate the top-N recommendations of courses appropriate to the students. Meanwhile, aL0 regularization term isexploited as the optimization strategywhich is established on the observation of the course items in the current recommendation system. The comparison experiments betweenstate-of-the-art methods and our approachare conducted to evaluate the performance of our method. Experimental results of different topics and number of courses both show that our proposed method outperforms state-of-the-art methods both in accuracy and efficiency.
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