Design and Implementation of an English Mobile Learning System Based on Weighted Naive Bayes

DOI

10.2991/978-94-6463-417-4_17How to use a DOI?

Keywords

Weighted Naive Bayes; English Mobile Learning System; Weight Distribution; Model Training

Abstract

This study employs the Weighted Naive Bayes algorithm in order to enhance the efficiency of personalized English learning in a mobile learning environment. By introducing a weighting factor, the traditional Naive Bayes classifier is optimized for an English mobile learning system design. Meanwhile, the application of the Naive Bayes algorithm and weighting techniques in mobile learning is analyzed in details, including algorithm selection, optimization, weight distribution, and model training. The results indicate that the English mobile learning system, optimized with the Weighted Naive Bayes algorithm, significantly improves learning outcomes, accuracy of personalized recommendations, and security of the learning process. Thus, it can effectively support English teaching and learning in a mobile learning environment.

Copyright

© 2024 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  - Ying Ye
PY  - 2024
DA  - 2024/05/07
TI  - Design and Implementation of an English Mobile Learning System Based on Weighted Naive Bayes
BT  - Proceedings of the 2024 5th International Conference on Big Data and Informatization Education (ICBDIE 2024)
PB  - Atlantis Press
SP  - 187
EP  - 196
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-417-4_17
DO  - 10.2991/978-94-6463-417-4_17
ID  - Ye2024
ER  -