Research on the Construction of Network Virtual Learning Community Models in the Context of Internet+

DOI

10.2991/978-94-6463-304-7_62How to use a DOI?

Keywords

online learning communities; user profiles; behavior sequences

Abstract

This study constructs user behavior models for virtual learning communities on the Internet to provide personalized services. The method involves preprocessing user data, feature extraction, and establishing models based on user profiles and behavior sequences. Results show the decision tree model reaches 82% accuracy. Augmenting less-represented data categories improves performance. The data-driven approach makes the model results more targeted compared to traditional research. This provides an effective method for user behavior analysis in constructing intelligent online learning communities.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhe Zhang
AU  - Youwen Zhang
PY  - 2023
DA  - 2023/12/04
TI  - Research on the Construction of Network Virtual Learning Community Models in the Context of Internet+
BT  - Proceedings of the 3rd International Conference on Digital Economy and Computer Application (DECA 2023)
PB  - Atlantis Press
SP  - 588
EP  - 594
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-304-7_62
DO  - 10.2991/978-94-6463-304-7_62
ID  - Zhang2023
ER  -