{"title":"数据挖掘技术在基于web的教学数据分析中的应用","authors":"M. Yao, Xi-zi Jin, Na Wang","doi":"10.1109/ITAPP.2010.5566101","DOIUrl":null,"url":null,"abstract":"In order to solve practical problems in network teaching data analysis ,the web-based instruction data of mathematical models and model framework was build .In the core process that data scoop out, the main adoption the classification method based on the continuity of data.It firstly gains the class-contained from the sample, and then obtains the standard category through the degree of support, finally marks the degree of strength among the inside members. This approach is only sensitive to the even distribution of the inside sample points, it does not require pre-set parameters . Using the clustering method analysis the web-based instruction data, the problem of web-based instruction data automatically cluster was solved.","PeriodicalId":116013,"journal":{"name":"2010 International Conference on Internet Technology and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using Data Mining Techniques in Web-Based Instruction Data Analysis\",\"authors\":\"M. Yao, Xi-zi Jin, Na Wang\",\"doi\":\"10.1109/ITAPP.2010.5566101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve practical problems in network teaching data analysis ,the web-based instruction data of mathematical models and model framework was build .In the core process that data scoop out, the main adoption the classification method based on the continuity of data.It firstly gains the class-contained from the sample, and then obtains the standard category through the degree of support, finally marks the degree of strength among the inside members. This approach is only sensitive to the even distribution of the inside sample points, it does not require pre-set parameters . Using the clustering method analysis the web-based instruction data, the problem of web-based instruction data automatically cluster was solved.\",\"PeriodicalId\":116013,\"journal\":{\"name\":\"2010 International Conference on Internet Technology and Applications\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Internet Technology and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITAPP.2010.5566101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Internet Technology and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITAPP.2010.5566101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Data Mining Techniques in Web-Based Instruction Data Analysis
In order to solve practical problems in network teaching data analysis ,the web-based instruction data of mathematical models and model framework was build .In the core process that data scoop out, the main adoption the classification method based on the continuity of data.It firstly gains the class-contained from the sample, and then obtains the standard category through the degree of support, finally marks the degree of strength among the inside members. This approach is only sensitive to the even distribution of the inside sample points, it does not require pre-set parameters . Using the clustering method analysis the web-based instruction data, the problem of web-based instruction data automatically cluster was solved.