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.
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Luo, Q., Pan, Z. (2007). Research on Personalized Community E-Learning Recommendation Service System by Using Improved Adaptive Filtering Algorithm. In: Hui, Kc., et al. Technologies for E-Learning and Digital Entertainment. Edutainment 2007. Lecture Notes in Computer Science, vol 4469. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73011-8_52
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DOI: https://doi.org/10.1007/978-3-540-73011-8_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73010-1
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