Research Article
English Teaching Ability Evaluation Algorithm Based on Big Data Fuzzy k-means Clustering
@INPROCEEDINGS{10.1007/978-3-030-87900-6_34, author={Jiayun Tang}, title={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 Cloud environment Data integration FCM MapReduce}, doi={10.1007/978-3-030-87900-6_34} }- Jiayun Tang
Year: 2021
English Teaching Ability Evaluation Algorithm Based on Big Data Fuzzy k-means Clustering
BIGIOT-EDU
Springer
DOI: 10.1007/978-3-030-87900-6_34
Abstract
Based on the rise of cloud applications and the use of various forms of digital devices, data is growing explosively. In the face of such a huge amount of data, the traditional data analysis tools only deal with the simple statistics, query and management of data, and can't deeply mine the potential useful information. Therefore, how to use big data to mine valuable information is particularly important. Clustering analysis is one of the big data analysis technologies. The traditional single machine clustering algorithm can not meet the requirements of big data information processing in terms of operational efficiency and computational complexity. The development of cloud computing technology provides a new research direction for big data clustering analysis. The English teaching comprehensive ability evaluation system can complete the evaluation and ranking of College English teaching comprehensive ability. By using the attribute method, seven attribute indexes are obtained. The example shows that the system has clear structure, reasonable process, and can flexibly adjust the evaluation parameters such as the scale of school scheme set and relevant psychological weight according to the user's requirements.
