Research on personalized community e-learning recommendation service system by using improved adaptive filtering algorithm

Authors:
Qi Luo;Pan Zhigeng
Affiliations:
Information Engineering School, Wuhan University of Science and Technology, Wuhan, China and School of Electrical Engineering, Wuhan Institute of technology, Wuhan, China;State Key Lab CAD&CG, ZheJiang University, Hangzhou, China
Venue:
Edutainment'07 Proceedings of the 2nd international conference on Technologies for e-learning and digital entertainment
Year:
2007

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Abstract

To meet the needs of education in the learning community, an improved adaptive filtering algorithm for teaching resources based on vector space model was proposed in the paper. First, feature selection and pseudo feedback were used to select the initial filtering profiles and thresholds through training algorithm. Then user feedback was utilized to modify the profiles and thresholds adaptively through filtering algorithm. The algorithm had two advantages, the first was that it could carry on self-study to improve the precision; the second was that the execution did not need massive initial texts in the process of filtering. The algorithm was also used in personalized Recommendation service system based on Community E-learning. The result manifested that the algorithm was effective.