Open interactive education algorithm based on cloud computing and big data. Issue 3 (18th May 2020) - Wei, Jing; Mo, Lianguang
In order to improve the self-learning ability of cloud computing and scheduling ability of big data resources in open interactive education, an open interactive education algorithm based on cloud computing and big data is proposed. An information flow model for open education big data is constructed, and big data mining is conducted to an open interactive education platform through the association rules mining method based on parallel scheduling to extract semantic ontology information feature quantity of interactive education; spatial attribute clustering is performed in the cloud computing environment according to the feature extraction results, and big data information is scheduled through the multi-feature weight allocation method. Simulation results show that in open interactive education, this method can cause relatively good output performance of big data mining, relatively high accuracy of feature information clustering of open interactive education and relatively strong feature resolution and recognition ability of data output, which meets the educational resource scheduling and allocation requirements of open education.