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Research On Student Behavior Analysis And Prediction Method Based On Campus Big Data

Posted on:2018-11-30Degree:MasterType:Thesis
Country:ChinaCandidate:Z LiangFull Text:PDF
GTID:2347330533966280Subject:Computer application technology
Abstract/Summary:PDF Full Text Request
Widespread deployment of campus one-card system in colleges and universities not only promote the construction of digital campus and facilitate the students' daily life greatly,but provide data to analyze student conduct and mining laws.Whereas,the management of numerous school is still using the traditional student management and service method which subdivides students through professional and grade,and adopting a simple management style,which cannot be carried out students personalized management and service in accordance with the characteristic behavior.In view of the above problems,this thesis studied and developed a student behavior analysis and prediction system based on the Spark by analyzing the characteristics of university campus big data,the following work is done:(1)Aiming at the problem of student behavior subdivision,the thesis,first designed the student behavior description index system,then,devised a student behavior segmentation model based on clustering analysis,and improved the traditional K-means clustering algorithms from two aspects that include the choice of initial clustering center and the number of clustering,proposed a K-means improved method based on density of optimization.In the Spark platform,parallelizing the improved method,applying it to student behavior Finally,the reliability of the results is verified by experiment.(2)For the rear and timeliness of student behavior reminded,the article has proposed K neighbor nonparametric regression forecasting model based on student behavior layered and solved the problems of the prediction larger error about K neighbor students forecasting model.Secondly,Using decision tree to give early warning analysis to the predictive results of the student behavior,has realized shift of the student behavior of rear emergency to front warning.Finally,in view of the serialized high time complexity problem of mass data processing,designing and implementing parallelization of the student behavior prediction and early warning algorithm under the Spark platform,at the same time,improving the efficiency of data processing and time performance.(3)On the basis of the above theoretical research,the thesis designed and implemented the student behavior analysis and prediction application platform based on Spark.Meanwhile,it introduces the construction,system design and development method of Spark big data platform in detail.The system,which has practical implications,developed in this article can offer a series of all-round behavior analysis and forecast functions,such as the students' consumption and learning,for students,colleges and the administrative department.
Keywords/Search Tags:Cluster Analysis, K-means, Prediction and early warning, Spark platform, Bigdata
PDF Full Text Request
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