{"title":"智能推理的数据工程","authors":"V. Lum, Sakti P. Ghosh","doi":"10.1109/ICDE.1987.7272383","DOIUrl":null,"url":null,"abstract":"As advanced applications become more and more demanding, the use of the data on hand becomes more and more sophisticated. In applications such as the kind in commercial banking environment, the search for data is rather simple and precise; the time constraints are not severe; statistical applications are not often used; history data is not so important; and estimates are not performed. In short, the demand to have an intelligent DB is at best minimal.","PeriodicalId":145433,"journal":{"name":"1987 IEEE Third International Conference on Data Engineering","volume":"634 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1987-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data engineering for intelligent inference\",\"authors\":\"V. Lum, Sakti P. Ghosh\",\"doi\":\"10.1109/ICDE.1987.7272383\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As advanced applications become more and more demanding, the use of the data on hand becomes more and more sophisticated. In applications such as the kind in commercial banking environment, the search for data is rather simple and precise; the time constraints are not severe; statistical applications are not often used; history data is not so important; and estimates are not performed. In short, the demand to have an intelligent DB is at best minimal.\",\"PeriodicalId\":145433,\"journal\":{\"name\":\"1987 IEEE Third International Conference on Data Engineering\",\"volume\":\"634 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1987-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1987 IEEE Third International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1987.7272383\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1987 IEEE Third International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1987.7272383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
As advanced applications become more and more demanding, the use of the data on hand becomes more and more sophisticated. In applications such as the kind in commercial banking environment, the search for data is rather simple and precise; the time constraints are not severe; statistical applications are not often used; history data is not so important; and estimates are not performed. In short, the demand to have an intelligent DB is at best minimal.
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