{"title":"An Alternative Extension of the FCM Algorithm for Clustering Fuzzy Databases","authors":"A. Touzi","doi":"10.1109/DBKDA.2010.35","DOIUrl":null,"url":null,"abstract":"Several real applications need to manage fuzzy information. Among the languages proposed for this type of data, the Fuzzy SQL (FSQL) language had a great success, seen its great power of modeling and it’s an extension of the well-known SQL language. In this paper, we propose an alternative for FCM algorithm For Fuzzy Database describe with FSQL. The conventional fuzzy clustering algorithms form fuzzy clusters so as to minimize the total distance from cluster centers to data points. However, they cannot be applied in the case where the data vectors are described with FSQL is given. To concretize our approach we used the BDRF described with the GEFRED model, which is supporting the FSQL language.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"303 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DBKDA.2010.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Several real applications need to manage fuzzy information. Among the languages proposed for this type of data, the Fuzzy SQL (FSQL) language had a great success, seen its great power of modeling and it’s an extension of the well-known SQL language. In this paper, we propose an alternative for FCM algorithm For Fuzzy Database describe with FSQL. The conventional fuzzy clustering algorithms form fuzzy clusters so as to minimize the total distance from cluster centers to data points. However, they cannot be applied in the case where the data vectors are described with FSQL is given. To concretize our approach we used the BDRF described with the GEFRED model, which is supporting the FSQL language.
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