Module advisor: a hybrid recommender system for elective module exploration.

RecSys '18: Twelfth ACM Conference on Recommender Systems Vancouver British Columbia Canada October, 2018(2018)

引用 7|浏览30
暂无评分
摘要
Recommender systems are omni-present in our every day lives, guiding us through the vast amount of information available. However, in the academic world, personalised recommendations are less prominent, leaving students to navigate through the typically large space of available courses and modules manually. Since it is crucial for students to make informed choices about their learning pathways, we aim to improve the way students discover elective modules by developing a hybrid recommender system prototype that is specifically designed to help students find elective modules from a diverse set of subjects. We can improve the discoverability of long-tail options and help students broaden their horizons by combining notions of similarity and diversity.
更多
查看译文
关键词
Recommender Systems, Content-based Filtering, Diversity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要