In order to optimise the effectiveness of resource recommendation and improve the coverage of personalised learning resource recommendation results, a personalised learning resource online recommendation method based on multidimensional feature extraction is proposed. Firstly, based on the feature expression and density parameters of user behaviour data, cluster the users. Secondly, extract users' time features, preference features, and learning resource features, and use feature matrices for efficient feature mining. Finally, the extracted personalised learning resource features are input int...
