{"title":"选择题中年龄和性别关系的可视化","authors":"Sanetoshi Yamada, Yoshiro Yamamoto","doi":"10.1109/ICTKE.2014.7001526","DOIUrl":null,"url":null,"abstract":"The information that customer data usually provides is the personal surface information including the sex, age and hometown. But, we can obtain personal internal information by analyzing questionnaire data. This paper, we propose the visualization that combined association analysis with correspondence analysis, it can find about difference of internal characteristic of six layers.","PeriodicalId":120743,"journal":{"name":"2014 Twelfth International Conference on ICT and Knowledge Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The visualization of relationship of age and gender to multiple choice questions\",\"authors\":\"Sanetoshi Yamada, Yoshiro Yamamoto\",\"doi\":\"10.1109/ICTKE.2014.7001526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The information that customer data usually provides is the personal surface information including the sex, age and hometown. But, we can obtain personal internal information by analyzing questionnaire data. This paper, we propose the visualization that combined association analysis with correspondence analysis, it can find about difference of internal characteristic of six layers.\",\"PeriodicalId\":120743,\"journal\":{\"name\":\"2014 Twelfth International Conference on ICT and Knowledge Engineering\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Twelfth International Conference on ICT and Knowledge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTKE.2014.7001526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Twelfth International Conference on ICT and Knowledge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTKE.2014.7001526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The visualization of relationship of age and gender to multiple choice questions
The information that customer data usually provides is the personal surface information including the sex, age and hometown. But, we can obtain personal internal information by analyzing questionnaire data. This paper, we propose the visualization that combined association analysis with correspondence analysis, it can find about difference of internal characteristic of six layers.
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