A Performance Weighted Collaborative Filtering algorithm for personalized radiology education.
Devising an accurate prediction algorithm that can predict the difficulty level of cases for individuals and then selects suitable cases for them is essential to the development of a personalized training system. In this paper, we propose a novel approach, called Performance Weighted Collaborative Filtering (PWCF), to predict the difficulty level of each case for individuals. The main idea of PWCF is to assign an optimal weight to each rating used for predicting the difficulty level of a target case for a trainee, rather than using an equal weight for all ratings as in traditional collaborative filtering methods. The assigned weight is a function of the performance level of the trainee at which the rating was made. The PWCF method and the traditional method are compared using two datasets. The experimental data are then evaluated by means of the MAE metric. Our experimental results show that PWCF outperforms the traditional methods by 8.12% and 17.05%, respectively, over the two datasets, in terms of prediction precision. This suggests that PWCF is a viable method for the development of personalized training systems in radiology education.
School of Information Science and Engineering, Key Laboratory for Embedded and Network Computing of Hunan Province, Hunan University, 410082 Changsha, China. Electronic address: hllin@hnu.edu.cn.
Hongli
H
Lin
Department of Computer Science, University of Regina, 3737 Wascana Parkway, Regina, SK S4S 0A2, Canada. Electronic address: xuedong.yang@uregina.ca.
Xuedong
X
Yang
School of Information Science and Engineering, Key Laboratory for Embedded and Network Computing of Hunan Province, Hunan University, 410082 Changsha, China.
Weisheng
W
Wang
School of Information Science and Engineering, Key Laboratory for Embedded and Network Computing of Hunan Province, Hunan University, 410082 Changsha, China.
Jiawei
J
Luo
D000465:Algorithms; D003194:Computer-Assisted Instruction / Q000379:methods*; D003299:Cooperative Behavior; D003952:Diagnostic Imaging; D004521:Educational Measurement / Q000379:methods*; D011871:Radiology / Q000193:education*; D014584:User-Computer Interface
Collaborative filtering; Performance weight; Personalized radiology education; Prediction algorithm