{"title":"Category of Fuzzy Operators in SQL","authors":"T. Memon, M.M.U. Ghani, N. Iftikhar","doi":"10.1109/ICET.2007.4516327","DOIUrl":null,"url":null,"abstract":"Current database management systems have their limitations when it comes to handling imprecise data. Several DBMS prototypes emerged in this regard by merging the laws of fuzzy set theory with different database models; but it has been observed that these systems could not gain much popularity because of the hesitation by users' to replace the conventional and reliable DBMS with them. Therefore, instead of developing a new fuzzy DBMS, the focus of this paper is to find a way to enhance the current database management systems, and enabling them to handle precise as well as imprecise data. The approach taken here for this purpose is to embed fuzziness in SQL language without changing its underlying structure. As a first step, a new category of operators is being introduced in SQL, naming Fuzzy Operators. The paper introduces two fuzzy operators - NEAR and NOT NEAR, explaining their working and the algorithms to implement them.","PeriodicalId":346773,"journal":{"name":"2007 International Conference on Emerging Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET.2007.4516327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Current database management systems have their limitations when it comes to handling imprecise data. Several DBMS prototypes emerged in this regard by merging the laws of fuzzy set theory with different database models; but it has been observed that these systems could not gain much popularity because of the hesitation by users' to replace the conventional and reliable DBMS with them. Therefore, instead of developing a new fuzzy DBMS, the focus of this paper is to find a way to enhance the current database management systems, and enabling them to handle precise as well as imprecise data. The approach taken here for this purpose is to embed fuzziness in SQL language without changing its underlying structure. As a first step, a new category of operators is being introduced in SQL, naming Fuzzy Operators. The paper introduces two fuzzy operators - NEAR and NOT NEAR, explaining their working and the algorithms to implement them.