Next Article in Journal
Semi-Supervised Classification Based on Low Rank Representation
Next Article in Special Issue
A Multi-Objective Harmony Search Algorithm for Sustainable Design of Floating Settlements
Previous Article in Journal
Affinity Propagation Clustering Using Path Based Similarity
Previous Article in Special Issue
Opposition-Based Adaptive Fireworks Algorithm
Article Menu

Export Article

Open AccessArticle
Algorithms 2016, 9(3), 47; doi:10.3390/a9030047

A Hybrid Course Recommendation System by Integrating Collaborative Filtering and Artificial Immune Systems

1
Software School, Nanchang University, Nanchang 330029, China
2
Innovation Center for Big Data & Digital Convergence and Department of Information Management, Yuan Ze University, Taoyuan 32026, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Javier Del Ser Lorente
Received: 27 April 2016 / Revised: 2 July 2016 / Accepted: 18 July 2016 / Published: 22 July 2016
(This article belongs to the Special Issue Metaheuristic Algorithms in Optimization and Applications)
View Full-Text   |   Download PDF [2118 KB, uploaded 25 July 2016]   |  

Abstract

This research proposes a two-stage user-based collaborative filtering process using an artificial immune system for the prediction of student grades, along with a filter for professor ratings in the course recommendation for college students. We test for cosine similarity and Karl Pearson (KP) correlation in affinity calculations for clustering and prediction. This research uses student information and professor information datasets of Yuan Ze University from the years 2005–2009 for the purpose of testing and training. The mean average error and confusion matrix analysis form the testing parameters. A minimum professor rating was tested to check the results, and observed that the recommendation systems herein provide highly accurate results for students with higher mean grades. View Full-Text
Keywords: course recommendation system; collaborative filtering; artificial immune system; confusion matrix; cluster analysis course recommendation system; collaborative filtering; artificial immune system; confusion matrix; cluster analysis
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chang, P.-C.; Lin, C.-H.; Chen, M.-H. A Hybrid Course Recommendation System by Integrating Collaborative Filtering and Artificial Immune Systems. Algorithms 2016, 9, 47.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top