Research on Course Recommendation Based on Rough Set

DOI

10.2991/icsnce-16.2016.71How to use a DOI?

Keywords

Course recommend; Similarity; Rough set; Cosine; MAE

Abstract

A credit system is the inexorable trend of higher education development. Course selection is the basis and core. Therefore, it is necessary to establish a reasonable course recommendation system. A method to recommend the course is used to guide students to choose the right course based on a large number of grades in the educational management system, and the K nearest neighbors are chosen to estimate score based on similarities between the student and the others. Reducing the attribute of datasets is one of the core contents in rough set theory. Remove the attributes that are not as important or redundant in knowledge property to improve the efficiency. The method is applied to the prediction of student grades using 3 different methods to discrete scores, the results show that the equal frequency algorithm is better than the others methods.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xueli Ren
AU  - Yubiao Dai
PY  - 2016/07
DA  - 2016/07
TI  - Research on Course Recommendation Based on Rough Set
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 365
EP  - 369
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.71
DO  - 10.2991/icsnce-16.2016.71
ID  - Ren2016/07
ER  -