{"title":"基于模糊本体的明尼苏达法规模型","authors":"N. Sram, M. Takács","doi":"10.1109/SAMI.2012.6208938","DOIUrl":null,"url":null,"abstract":"The Minnesota Code is a hierarchical rule-based system for the evaluation of reference ECG signals. One of its weaknesses is the crisp value based hierarchy system. The proper and effective modeling of the rule hierarchy is the key point of the Minnesota Code. In this paper the authors present a possible method to improve the decision model of the Minnesota Code by applying fuzzy ontology to represent the decision process as a hierarchical description of important classes (concepts) along with the description of the properties (of the instances) of each concept.","PeriodicalId":158731,"journal":{"name":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fuzzy ontology-based model for the Minnesota Code\",\"authors\":\"N. Sram, M. Takács\",\"doi\":\"10.1109/SAMI.2012.6208938\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Minnesota Code is a hierarchical rule-based system for the evaluation of reference ECG signals. One of its weaknesses is the crisp value based hierarchy system. The proper and effective modeling of the rule hierarchy is the key point of the Minnesota Code. In this paper the authors present a possible method to improve the decision model of the Minnesota Code by applying fuzzy ontology to represent the decision process as a hierarchical description of important classes (concepts) along with the description of the properties (of the instances) of each concept.\",\"PeriodicalId\":158731,\"journal\":{\"name\":\"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"volume\":\"114 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAMI.2012.6208938\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAMI.2012.6208938","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Minnesota Code is a hierarchical rule-based system for the evaluation of reference ECG signals. One of its weaknesses is the crisp value based hierarchy system. The proper and effective modeling of the rule hierarchy is the key point of the Minnesota Code. In this paper the authors present a possible method to improve the decision model of the Minnesota Code by applying fuzzy ontology to represent the decision process as a hierarchical description of important classes (concepts) along with the description of the properties (of the instances) of each concept.