Research Article
Research on English Teaching Ability Evaluation Algorithm Based on Big Data Fuzzy k-means Clustering
@INPROCEEDINGS{10.1007/978-3-030-87900-6_58, author={Ying Xu}, title={Research on English Teaching Ability Evaluation Algorithm Based on Big Data Fuzzy k-means Clustering}, proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1--3, 2021, Proceedings, Part I}, proceedings_a={BIGIOT-EDU}, year={2021}, month={10}, keywords={Big data English teaching Teaching ability evaluation Information fusion Data clustering}, doi={10.1007/978-3-030-87900-6_58} }
- Ying Xu
Year: 2021
Research on English Teaching Ability Evaluation Algorithm Based on Big Data Fuzzy k-means Clustering
BIGIOT-EDU
Springer
DOI: 10.1007/978-3-030-87900-6_58
Abstract
Aiming at the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, an English teaching ability evaluation algorithm based on big data fuzzy k-means clustering and information fusion is proposed. Firstly, the constraint parameter index analysis model is established; secondly, the quantitative recursive analysis method is used to evaluate the ability of big data information model, and the entropy feature extraction of the ability constraint feature information is realized; finally, the big data information fusion and K-means clustering algorithm are integrated to realize the index parameter clustering and integration of English teaching ability, and the corresponding teaching resource allocation plan is compiled, To realize the evaluation of English teaching ability. The experimental results show that this method has better ability of information fusion and analysis, and improves the accuracy of teaching ability evaluation and the efficiency of teaching resource application.