Research And Application Of Multidimensional Analysis Method Of Higher Education Data

In order to meet the demand of the third industrial revolution for high-quality talents,universities with the main functions of personnel training constantly explore the talent training model,apply information technology to assist teaching management and teaching reform,which accelerates the construction of smart campus.In the process of the development of information technology in colleges and universities,it has been very meaningful to fully accumulate and use these data to improve teaching management.At present,the mining of university data is mostly realized by association rules mining algorithm.However,the association rule mining algorithm has the problems of low efficiency,less data dimension and less accuracy.In order to improve the accuracy and efficiency of the algorithm,this thesis proposes a HMApriori algorithm which combining hash function and mark transaction compression.Based on HMApriroi algorithm and OLAP technology,a multi-dimensional association rule mining method is designed.The specific research contents are as follows:(1)The HMApriori algorithm combining hash function and mark transaction compression is proposed,which solves the shortcomings of excessive and redundant Apriori algorithm candidate set.In this thesis,the Apriori algorithm,HMApriori algorithm and other improved algorithms are compared in the student course data set.Experiments show that the HMApriori algorithm proposed in this thesis has achieved significant improvement in the number and timing of candidate 2 items.(2)This thesis designs a multidimensional association rules mining method which combines the hmaporiori algorithm and OLAP technology,and uses this method to mine the personal information,online information,book borrowing information and other multi-dimensional data of students,and analyzes the relationship between the multi-dimensional data and academic achievements.(3)Constructed the academic analysis system,applied HMApriori algorithm and multi-dimensional association rule mining method to the system.Through the statistical analysis and correlation analysis module,the overall situation of the students in the school and the factors affecting the students' performance were respectively displayed.The system can assist managers in making decisions,improve teaching management,and help students adjust their learning progress.After the system is developed,it has universality and can be promoted and used in various universities in China,which has great application value.