{"title":"支持粗糙集理论在非常大的数据库使用oracle RDBMS","authors":"R. Chen, T.Y. Lin","doi":"10.1109/AFSS.1996.583625","DOIUrl":null,"url":null,"abstract":"Earlier a \"new\" rough set theory for very large databases was proposed by T.Y. Lin (1996). In this paper the authors attempt to evaluate the performance of such a rough set theory for a very large database. ORACLE, a relational database management system (RDBMS), is the market leader in open system databases. Windows NT has been growing into the data server environment and is a strong contender for decision support system applications with its open and cost-effective architecture. So ORACLE running under Windows NT was used in this report. The main goal of this research is to formulate a suitable rough set theory for very large databases.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"249 24","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Supporting rough set theory in very large databases using oracle RDBMS\",\"authors\":\"R. Chen, T.Y. Lin\",\"doi\":\"10.1109/AFSS.1996.583625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Earlier a \\\"new\\\" rough set theory for very large databases was proposed by T.Y. Lin (1996). In this paper the authors attempt to evaluate the performance of such a rough set theory for a very large database. ORACLE, a relational database management system (RDBMS), is the market leader in open system databases. Windows NT has been growing into the data server environment and is a strong contender for decision support system applications with its open and cost-effective architecture. So ORACLE running under Windows NT was used in this report. The main goal of this research is to formulate a suitable rough set theory for very large databases.\",\"PeriodicalId\":197019,\"journal\":{\"name\":\"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium\",\"volume\":\"249 24\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AFSS.1996.583625\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AFSS.1996.583625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Supporting rough set theory in very large databases using oracle RDBMS
Earlier a "new" rough set theory for very large databases was proposed by T.Y. Lin (1996). In this paper the authors attempt to evaluate the performance of such a rough set theory for a very large database. ORACLE, a relational database management system (RDBMS), is the market leader in open system databases. Windows NT has been growing into the data server environment and is a strong contender for decision support system applications with its open and cost-effective architecture. So ORACLE running under Windows NT was used in this report. The main goal of this research is to formulate a suitable rough set theory for very large databases.
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