{"title":"基于可视化数据挖掘工具的学历趋势分析","authors":"Nittaya Kerdprasop, Kittisak Kerdprasop","doi":"10.1109/UMEDIA.2015.7297451","DOIUrl":null,"url":null,"abstract":"We present in this paper the analysis results of prominent educational characteristics differentiating people from the two regions in the world: advanced economies versus east Asia and the pacific countries. The automatic multivariate analysis of classification trends has been demonstrated through the visual data mining tool called KNIME. We found from the empirical studies that from the years 1950 to 1980, percentage of population with no education is the sole factor accurately classifying advanced economies from the east Asia and pacific nations. But since the 1985 until 2010, the classification models have been shifted toward other four factors: (1) average years of schooling attained, (2) percentage of population completing primary school, (3) average years of tertiary schooling attained, and (4) percentage of population completing tertiary school. We illustrate graphical decision tree models of all 5-year intervals since 1950 to 2010.","PeriodicalId":262562,"journal":{"name":"2015 8th International Conference on Ubi-Media Computing (UMEDIA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Educational attainment trend analysis with the visual data mining tool\",\"authors\":\"Nittaya Kerdprasop, Kittisak Kerdprasop\",\"doi\":\"10.1109/UMEDIA.2015.7297451\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present in this paper the analysis results of prominent educational characteristics differentiating people from the two regions in the world: advanced economies versus east Asia and the pacific countries. The automatic multivariate analysis of classification trends has been demonstrated through the visual data mining tool called KNIME. We found from the empirical studies that from the years 1950 to 1980, percentage of population with no education is the sole factor accurately classifying advanced economies from the east Asia and pacific nations. But since the 1985 until 2010, the classification models have been shifted toward other four factors: (1) average years of schooling attained, (2) percentage of population completing primary school, (3) average years of tertiary schooling attained, and (4) percentage of population completing tertiary school. We illustrate graphical decision tree models of all 5-year intervals since 1950 to 2010.\",\"PeriodicalId\":262562,\"journal\":{\"name\":\"2015 8th International Conference on Ubi-Media Computing (UMEDIA)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 8th International Conference on Ubi-Media Computing (UMEDIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UMEDIA.2015.7297451\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Conference on Ubi-Media Computing (UMEDIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UMEDIA.2015.7297451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Educational attainment trend analysis with the visual data mining tool
We present in this paper the analysis results of prominent educational characteristics differentiating people from the two regions in the world: advanced economies versus east Asia and the pacific countries. The automatic multivariate analysis of classification trends has been demonstrated through the visual data mining tool called KNIME. We found from the empirical studies that from the years 1950 to 1980, percentage of population with no education is the sole factor accurately classifying advanced economies from the east Asia and pacific nations. But since the 1985 until 2010, the classification models have been shifted toward other four factors: (1) average years of schooling attained, (2) percentage of population completing primary school, (3) average years of tertiary schooling attained, and (4) percentage of population completing tertiary school. We illustrate graphical decision tree models of all 5-year intervals since 1950 to 2010.