Research Article
Multimedia self-learning behavior monitoring data mining system based on Web
@INPROCEEDINGS{10.4108/eai.27-8-2020.2294666, author={Chun-Sheng DENG and Hai-Bo CHENG and Jian-Ming LIN and Ju-Rong YANG and Yan-Chen ZHU}, title={Multimedia self-learning behavior monitoring data mining system based on Web}, proceedings={Proceedings of the 13th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2020, 27-28 August 2020, Cyberspace}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2020}, month={11}, keywords={data mining; autonomous learning; k-means algorithm; correlation mining}, doi={10.4108/eai.27-8-2020.2294666} }- Chun-Sheng DENG
Hai-Bo CHENG
Jian-Ming LIN
Ju-Rong YANG
Yan-Chen ZHU
Year: 2020
Multimedia self-learning behavior monitoring data mining system based on Web
MOBIMEDIA
EAI
DOI: 10.4108/eai.27-8-2020.2294666
Abstract
In view of the poor clustering effect of information data in the use of the original English multimedia independent learning behavior monitoring data mining system, the original data mining system is optimized according to the Web architecture, and a web-based English multimedia independent learning behavior monitoring data mining system was designed. Install the monitoring sensor, data transmission channel and decoder into the original system hardware framework to complete the system hardware design; According to the requirements of Web architecture design, this paper constructs the English multimedia independent learning behavior monitoring database, adopts the data feature point extraction algorithm, and uses the Web mining technology to achieve the system data mining performance, so as to realize the design of the web-based English multimedia independent learning behavior monitoring data mining system. Through the comparison of data clustering effect, it is verified that the designed system can effectively improve the ability of data clustering and improve the performance of system data mining.