{"title":"基于贝叶斯网络的小规模私立大学辍学行为模式建模","authors":"Naruhiko Shiratori","doi":"10.1109/IIAI-AAI.2017.178","DOIUrl":null,"url":null,"abstract":"In this study, we combine the whole student model and the individual student model to express three kinds of dropping behavior, heterogeneity of the dropping behavior and temporal heterogeneity. The model constructed in this research is still a skeleton model, In the future, quantitative survey, statistical learning should be conducted, learning and expression of graph structure and quantitative relation are required.","PeriodicalId":281712,"journal":{"name":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Modeling Dropout Behavior Patterns Using Bayesian Networks in Small-Scale Private University\",\"authors\":\"Naruhiko Shiratori\",\"doi\":\"10.1109/IIAI-AAI.2017.178\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, we combine the whole student model and the individual student model to express three kinds of dropping behavior, heterogeneity of the dropping behavior and temporal heterogeneity. The model constructed in this research is still a skeleton model, In the future, quantitative survey, statistical learning should be conducted, learning and expression of graph structure and quantitative relation are required.\",\"PeriodicalId\":281712,\"journal\":{\"name\":\"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIAI-AAI.2017.178\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2017.178","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling Dropout Behavior Patterns Using Bayesian Networks in Small-Scale Private University
In this study, we combine the whole student model and the individual student model to express three kinds of dropping behavior, heterogeneity of the dropping behavior and temporal heterogeneity. The model constructed in this research is still a skeleton model, In the future, quantitative survey, statistical learning should be conducted, learning and expression of graph structure and quantitative relation are required.