Cross-Dimension Mining Model of Public Opinion Data in Online Education Based on Fuzzy Association Rules
Peer reviewed, Journal article
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Original versionLi, L.-x., Huo, Y., & Lin, J. C.-W. (2021). Cross-Dimension Mining Model of Public Opinion Data in Online Education Based on Fuzzy Association Rules. Mobile Networks and Applications. 10.1007/s11036-021-01769-7
The multi-dimensional characteristics of public opinion in online education lead to the difficulty of data cross-dimensional mining. To solve this problem, this paper designs a cross-dimensional data mining model of public opinion in online education based on fuzzy association rules. Based on the public opinion subject, object, and ontology to analyze the characteristics of public opinion in online education, Yaahp software is used to calculate the influence factor weight of public opinion in online education. According to the weight analysis results, the relationship between the dimensions of various public opinion data is clarified by using data semantic association. This paper introduces the fuzzy set theory into the database and uses crawlers to obtain public opinion data and stores them in the database, to complete the data preprocessing through distributed text preprocessing, feature selection distributed computing, and text vectorization distributed computing. Taking the cloud computing platform as the core, the cross-dimension mining model of public opinion in online education data is constructed according to the dimension correlation analysis and preprocessing results. The simulation results show that the model has the advantages of wide range, fast speed, and high accuracy, and can provide data support for education reform.