A key feature mining method of online teaching behaviour based on k-kernel decomposition Online publication date: Mon, 08-Jul-2024
by Wei Wang
International Journal of Information and Communication Technology (IJICT), Vol. 25, No. 1, 2024
Abstract: In view of the poor effect of online teaching behaviour key feature mining, an online teaching behaviour key feature mining method based on k-kernel decomposition is designed. Firstly, the adjacent data of the key features of network teaching behaviour are interpolated to determine the key features, and the singular distance function is normalised to complete the feature preprocessing. Then, the key characteristics of network teaching behaviour are transformed into weighted network, and the key characteristics are divided according to the centrality of nodes. Finally, the online behaviour feature k-kernel after classification is assigned, the feature k-kernel value index after assignment is calculated, the correlation of feature data is calculated, the probability of feature data belonging to k-clustering is determined, and the key feature mining of network teaching behaviour is completed. The results show that the mining effect of this method is good.
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