{"title":"Elimination of semantic ambiguity in fuzzy relational models","authors":"M. Nakata","doi":"10.1109/ISUMA.1995.527770","DOIUrl":null,"url":null,"abstract":"A generalized possibility-distribution-fuzzy-relational-model is proposed considering semantic ambiguity for values of membership attribute and ambiguity contained in values of membership attribute. Then the extended relational algebra is shown. In order to eliminate the semantic ambiguity, the concept of membership is introduced into each attribute. This clarifies the origin of membership attribute values. What the value of membership means depends on the property of attributes. In order to eliminate ambiguity contained in values of membership attribute those values are expressed by fuzzy values. This clarifies what relationships fuzzy data values have with their membership attribute values. Therefore there is no semantic ambiguity for the values of membership attributes and no ambiguity in the values of membership attributes in our extended relational model.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISUMA.1995.527770","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A generalized possibility-distribution-fuzzy-relational-model is proposed considering semantic ambiguity for values of membership attribute and ambiguity contained in values of membership attribute. Then the extended relational algebra is shown. In order to eliminate the semantic ambiguity, the concept of membership is introduced into each attribute. This clarifies the origin of membership attribute values. What the value of membership means depends on the property of attributes. In order to eliminate ambiguity contained in values of membership attribute those values are expressed by fuzzy values. This clarifies what relationships fuzzy data values have with their membership attribute values. Therefore there is no semantic ambiguity for the values of membership attributes and no ambiguity in the values of membership attributes in our extended relational model.