Home > Archive > 2019 > Volume 9 Number 5 (Oct. 2019) >
IJMLC 2019 Vol.9(5): 621-628 ISSN: 2010-3700
DOI: 10.18178/ijmlc.2019.9.5.849

The Research of Intelligent Virtual Learning Community

Bo Song and Xiaomei Li

Abstract—At present, there are some problems in the way of research and training of primary school teachers, such as high cost, long cycle, limited number of research and training, slow updating of research contents and so on. Therefore, the virtual learning community for primary school teachers' research and training is constructed. In the process of implementation community core function, a hybrid recommendation algorithm based on content information label extraction and collaborative filtering is proposed for personalized recommendation system, which solves the problem of cold start of new users. Based on the NLP and the deep-learning algorithms, the two models of interest and behaviour are combined to update the interest model based on the behaviour of the learners in the intelligent teaching system. According to the user evaluation data, the intelligent teaching evaluation system has realized the intelligent evaluation of teachers' teaching activities. The insufficient in problem classification have been improved based on deep-learning algorithms for intelligent question answering system. The solution proposed in this paper has been applied to the research and training of primary school teachers in Liaoning province of China, which will play an important role in improving the level of teachers in primary education.

Index Terms—VLC, teachers' research and training, NLP, deep learning.

Bo Song is with Software College of Shenyang Normal University, China (e-mail: songbo63@aliyun.com).
Xiaomei Li is with Liaoning Research and Training Centre for Basic Education, China (e-mail: 1715500576@qq.com).

[PDF]

Cite: Bo Song and Xiaomei Li, "The Research of Intelligent Virtual Learning Community," International Journal of Machine Learning and Computing vol. 9, no. 5, pp. 621-628, 2019.

Copyright © 2019 by the authors. 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).

 

General Information

  • E-ISSN: 2972-368X
  • Abbreviated Title: Int. J. Mach. Learn.
  • Frequency: Quaterly
  • DOI: 10.18178/IJML
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Inspec (IET), Google Scholar, Crossref, ProQuest, Electronic Journals LibraryCNKI.
  • E-mail: ijml@ejournal.net


Article Metrics in Dimensions