Research on Grouping Strategy of Virtual Learning Community Based on the Fuzzy C-means Clustering
- DOI
- 10.2991/icacie-16.2016.2How to use a DOI?
- Keywords
- virtual learning community, the fuzzy c-means clustering algorithm, learning characteristic, teaching strategy reasoning mechanism
- Abstract
Virtual learning community, as a new model of network education, is widely used in the process of learning. But this kind of way is not gradually satisfying people's needs for more intelligent and personalized. Teaching strategy in virtual learning community is an important research direction of intelligent reasoning and it is the key to realize intelligent which has great role in promoting for it. In this paper, the fuzzy c-means clustering algorithm is applied to analysis of the characteristics of learning and grouped from the perspective of teaching strategy and reasoning in virtual learning community. And the model of teaching strategy reasoning mechanism based on learning characteristics is designed which use the cosine similarity and grouping clustering center vector and teaching part of the matching degree of policy rule conditions by setting the threshold of matching processing. Formulate specific feasible learning tasks and teaching strategies will be made for the learners. Through the simulation experiments it is found that the teaching strategy reasoning algorithm is feasible and it has achieved good results.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yan Cheng AU - Jianhua Xie AU - Weisheng Xu PY - 2016/10 DA - 2016/10 TI - Research on Grouping Strategy of Virtual Learning Community Based on the Fuzzy C-means Clustering BT - Proceedings of the 2016 International Conference on Automatic Control and Information Engineering PB - Atlantis Press SP - 7 EP - 11 SN - 2352-5401 UR - https://doi.org/10.2991/icacie-16.2016.2 DO - 10.2991/icacie-16.2016.2 ID - Cheng2016/10 ER -